Kaiserslautern - Fachbereich Informatik
Refine
Year of publication
Document Type
- Preprint (346) (remove)
Has Fulltext
- yes (346)
Keywords
- AG-RESY (17)
- Case-Based Reasoning (16)
- RODEO (10)
- Fallbasiertes Schliessen (9)
- Case Based Reasoning (6)
- Abstraction (5)
- Fallbasiertes Schließen (5)
- Robotics (5)
- case-based problem solving (5)
- CoMo-Kit (4)
Faculty / Organisational entity
A new and systematic basic approach to force- and vision-based robot manipulation of deformable (non-rigid) linear objects is introduced. This approach reduces the computational needs by using a simple state-oriented model of the objects. These states describe the relation between the deformable and rigid obstacles, and are derived from the object image and its features. We give an enumeration of possible contact states and discuss the main characteristics of each state. We investigate the performance of robust transitions between the contact states and derive criteria and conditions for each of the states and for two sensor systems, i.e. a vision sensor and a force/torque sensor. This results in a new and task-independent approach in regarding the handling of deformable objects and in a sensor-based implementation of manipulation primitives for industrial robots. Thus, the usage of sensor processing is an appropriate solution for our problem. Finally, we apply the concept of contact states and state transitions to the description of a typical assembly task. Experimental results show the feasibility of our approach: A robot performs several contact state transitions which can be combined for solving a more complex task.
Building interoperation among separately developed software units requires checking their conceptual assumptions and constraints. However, eliciting such assumptions and constraints is time consuming and is a challenging task as it requires analyzing each of the interoperating software units. To address this issue we proposed a new conceptual interoperability analysis approach which aims at decreasing the analysis cost and the conceptual mismatches between the interoperating software units. In this report we present the design of a planned controlled experiment for evaluating the effectiveness, efficiency, and acceptance of our proposed conceptual interoperability analysis approach. The design includes the study objectives, research questions, statistical hypotheses, and experimental design. It also provides the materials that will be used in the execution phase of the planned experiment.
This paper deals with the handling of deformable linear objects (DLOs), such as hoses, wires, or leaf springs. It investigates usable features for the vision-based detection of a changing contact situation between a DLO and a rigid polyhedral obstacle and a classification of such contact state transitions. The result is a complete classification of contact state transitions and of the most significant features for each class. This knowledge enables reliable detection of changes in the DLO contact situation, facilitating implementation of sensor-based manipulation skills for all possible contact changes.
A growing share of all software development project work is being done by geographically distributed teams. To satisfy shorter product design cycles, expert team members for a development project may need to be r ecruited globally. Yet to avoid extensive travelling or r eplacement costs, distributed project work is preferred. Current-generation software engineering tools and ass ociated systems, processes, and methods were for the most part developed to be used within a single enterprise. Major innovations have lately been introduced to enable groupware applications on the Internet to support global collaboration. However, their deployment for distributed software projects requires further research. In partic ular, groupware methods must seamlessly be integrated with project and product management systems to make them attractive for industry. In this position paper we outline the major challenges concerning distributed (virtual) software projects. Based on our experiences with software process modeling and enactment environments, we then propose approaches to solve those challenges.
Evaluation is an important issue for every scientific field and a necessity for an emerging soft-ware technology like case- based reasoning. This paper is a supplementation to the review of industrial case-based reasoning tools by K.-D. Althoff, E. Auriol, R. Barletta and M. Manago which describes the most detailed evaluation of commercial case-based reasoning tools currently available. The author focuses on some important aspects that correspond to the evaluation ofcase-based reasoning systems and gives links to ongoing research.
Case-Based Reasoning for Decision Support and Diagnostic Problem Solving: The INRECA Approach
(1995)
INRECA offers tools and methods for developing, validating, and maintaining decision support systems. INRECA's basic technologies are inductive and case-based reasoning, namely KATE -INDUCTION (cf., e.g., Manago, 1989; Manago, 1990) and S3-CASE, a software product based on PATDEX (cf., e.g., Wess,1991; Richter & Wess, 1991; Althoff & Wess, 1991). Induction extracts decision knowledge from case databases. It brings to light patterns among cases and helps monitoring trends over time. Case-based rea -soning relates the engineer's current problem to past experiences.
MOLTKE is a research project dealing with a complex technical application. After describing the domain of CNCmachining centers and the applied KA methods, we summarize the concrete KA problems which we have to handle. Then we describe a KA mechanism which supports an engineer in developing a diagnosis system. In chapter 6 weintroduce learning techniques operating on diagnostic cases and domain knowledge for improving the diagnostic procedure of MOLTKE. In the last section of this chapter we outline some essential aspects of organizationalknowledge which is heavily applied by engineers for analysing such technical systems (Qualitative Engineering). Finally we give a short overview of the actual state of realization and our future plans.
In this paper we will present a design model (in the sense of KADS) for the domain of technical diagnosis. Based on this we will describe the fully implemented expert system shell MOLTKE 3.0, which integrates common knowledge acquisition methods with techniques developed in the fields of Model-Based Diagnosis and Machine Learning, especially Case-Based Reasoning.
Case-based knowledge acquisition, learning and problem solving for diagnostic real world tasks
(1999)
Within this paper we focus on both the solution of real, complex problems using expert system technology and the acquisition of the necessary knowledge from a case-based reasoning point of view. The development of systems which can be applied to real world problems has to meet certain requirements. E.g., all available information sources have to be identified and utilized. Normally, this involves different types of knowledge for which several knowledge representation schemes are needed, because no scheme is equally natural for all sources. Facing empirical knowledge it is important to complement the use of manually compiled, statistic and otherwise induced knowledge by the exploitation of the intuitive understandability of case-based mechanisms. Thus, an integration of case-based and alternative knowledge acquisition and problem solving mechanisms is necessary. For this, the basis is to define the "role" which case-based inference can "play" within a knowledge acquisition workbench. We will discuss a concrete casebased architecture, which has been applied to technical diagnosis problems, and its integration into a knowledge acquisition workbench which includes compiled knowledge and explicit deep models, additionally.
Im Bereich der Expertensysteme ist das Problemlösen auf der Basis von Fallbeispielen ein derzeit sehr aktuelles Thema. Da sich sehr unterschiedliche Fachgebiete und Disziplinen hiermit auseinandersetzen, existiert allerdings eine entsprechende Vielfalt an Begriffen und Sichten auf fallbasiertes Problemlösen. In diesem Beitrag werden wir einige für das fallbasierte Problemlösen wichtige Begriffe präzisieren bzw. begriffliche Zusammenhänge aufdecken. Die dabei verfolgte Leitlinie ist weniger die, ein vollständiges Begriffsgebäude zu entwickeln, sondern einen ersten Schritt in Richtung eines einfachen Beschreibungsrahmens zu gehen, um damit den Vergleich verschiedener Ansätze und Systeme zu ermöglichen. Auf dieser Basis wird dann der derzeitige Stand der Forschung am Beispiel konkreter Systeme zur fallbasierten Diagnose dargelegt. Den Abschluss bildet eine Darstellung bislang offener Fragen und interessanter Forschungsziele.
Fallbasiertes Schliessen ist ein derzeit viel diskutierter Problemlösesansatz. Dieser Beitrag gibt einen Überblick über den aktuellen Stand der Forschung auf diesem Gebiet, insbesondere im Hinblick auf die Entwicklung von Expertensystemen (einen ersten Schritt in diese Richtung stellte bereits der Beitrag von Bartsch-Spörl, [BS87] dar). Dazu stellen wir die dem fallbasierten Schliessen zugrundeliegenden Mechanismen vor. Ergänzt wird dies durch den Vergleich mit alternativen Verfahren wie z.B. regelbasiertes, analoges und induktives Schliessen sowie eine ausführliche Literaturübersicht.
Retrieval of cases is one important step within the case-based reasoning paradigm. We propose an improvement of this stage in the process model for finding most similar cases with an average effort of O[log2n], n number of cases. The basic idea of the algorithm is to use the heterogeneity of the search space for a density-based structuring and to employ this precomputed structure, a k-d tree, for efficient case retrieval according to a given similarity measure sim. In addition to illustrating the basic idea, we present the expe- rimental results of a comparison of four different k-d tree generating strategies as well as introduce the notion of virtual bounds as a new one that significantly reduces the retrieval effort from a more pragmatic perspective. The presented approach is fully implemented within the (Patdex) system, a case-based reasoning system for diagnostic applications in engineering domains.
PANDA is a run-time package based on a very small operating system kernel which supports distributed applications written in C++. It provides powerful abstractions such as very efficient user-level threads, a uniform global address space, object and thread mobility, garbage collection, and persistent objects. The paper discusses the design ration- ales underlying the PANDA system. The fundamental features of PANDA are surveyed, and their implementation in the current prototype environment is outlined.
Distributed systems are an alternative to shared-memorymultiprocessors for the execution of parallel applications.PANDA is a runtime system which provides architecturalsupport for efficient parallel and distributed program-ming. PANDA supplies means for fast user-level threads,and for a transparent and coordinated sharing of objectsacross a homogeneous network. The paper motivates themajor architectural choices that guided our design. Theproblem of sharing data in a distributed environment isdiscussed, and the performance of appropriate mecha-nisms provided by the PANDA prototype implementation isassessed.
As the properties of components have gradually become clearer, attention has started to turn to the architectural issues which govern their interaction and composition. In this paper we identify some of the major architectural questions affecting component-based software develop-ment and describe the predominant architectural dimensions. Of these, the most interesting is the "architecture hierarchy" which we believe is needed to address the "interface vicissitude" problem that arises whenever interaction refinement is explicitly documented within a component-based system. We present a solution to this problem based on the concept of stratified architectures and object metamorphosis Finally, we describe how these concepts may assist in increasing the tailorability of component-based frameworks.
This paper presents a new kind of abstraction, which has been developed for the purpose of proofplanning. The basic idea of this paper is to abstract a given theorem and to find an abstractproof of it. Once an abstract proof has been found, this proof has to be refined to a real proofof the original theorem. We present a goal oriented abstraction for the purpose of equality proofplanning, which is parameterized by common parts of the left- and right-hand sides of the givenequality. Therefore, this abstraction technique provides an abstract equality problem which ismore adequate than those generated by the abstractions known so far. The presented abstractionalso supports the heuristic search process based on the difference reduction paradigm. We give aformal definition of the abstract space including the objects and their manipulation. Furthermore,we prove some properties in order to allow an efficient implementation of the presented abstraction.
Simultaneous quantifier elimination in sequent calculus is an improvement over the well-known skolemization. It allows a lazy handling of instantiations as well as of the order of certain reductions. We prove the soundness of a sequent calculus which incorporates a rule for simultaneous quantifier elimination. The proof is performed by semantical arguments and provides some insights into the dependencies between various formulas in a sequent.
This report contains a collection of abstracts for talks given at the "Deduktionstreffen" held at Kaiserslautern, October 6 to 8, 1993. The topics of the talks range from theoretical aspects of term rewriting systems and higher order resolution to descriptions of practical proof systems in various applications. They are grouped together according the following classification: Distribution and Combination of Theorem Provers, Termination, Completion, Functional Programs, Inductive Theorem Proving, Automatic Theorem Proving, Proof Presentation. The Deduktionstreffen is the annual meeting of the Fachgruppe Deduktionssysteme in the Gesellschaft für Informatik (GI), the German association for computer science.
In this paper we show that distributing the theorem proving task to several experts is a promising idea. We describe the team work method which allows the experts to compete for a while and then to cooperate. In the cooperation phase the best results derived in the competition phase are collected and the less important results are forgotten. We describe some useful experts and explain in detail how they work together. We establish fairness criteria and so prove the distributed system to be both, complete and correct. We have implementedour system and show by non-trivial examples that drastical time speed-ups are possible for a cooperating team of experts compared to the time needed by the best expert in the team.
We study deterministic conditional rewrite systems, i.e. conditional rewrite systemswhere the extra variables are not totally free but 'input bounded'. If such a systemR is quasi-reductive then !R is decidable and terminating. We develop a critical paircriterion to prove confluence if R is quasi-reductive and strongly deterministic. In thiscase we prove that R is logical, i.e./!R==R holds. We apply our results to proveHorn clause programs to be uniquely terminating.This research was supported by the Deutsche Forschungsgemeinschaft, SFB 314, Project D4
We investigate one of the classical problems of the theory ofterm rewriting, namely termination. We present an ordering for compar-ing higher-order terms that can be utilized for testing termination anddecreasingness of higher-order conditional term rewriting systems. Theordering relies on a first-order interpretation of higher-order terms anda suitable extension of the RPO.
In this paper we are interested in an algebraic specification language that (1) allowsfor sufficient expessiveness, (2) admits a well-defined semantics, and (3) allows for formalproofs. To that end we study clausal specifications over built-in algebras. To keep thingssimple, we consider built-in algebras only that are given as the initial model of a Hornclause specification. On top of this Horn clause specification new operators are (partially)defined by positive/negative conditional equations. In the first part of the paper wedefine three types of semantics for such a hierarchical specification: model-theoretic,operational, and rewrite-based semantics. We show that all these semantics coincide,provided some restrictions are met. We associate a distinguished algebra A spec to ahierachical specification spec. This algebra is initial in the class of all models of spec.In the second part of the paper we study how to prove a theorem (a clause) valid in thedistinguished algebra A spec . We first present an abstract framework for inductive theoremprovers. Then we instantiate this framework for proving inductive validity. Finally wegive some examples to show how concrete proofs are carried out.This report was supported by the Deutsche Forschungsgemeinschaft, SFB 314 (D4-Projekt)
This paper discusses the benefits and drawbacks of caching and replication strategies in the WWW with respect to the Internet infrastructure. Bandwidth consumption, latency, and overall error rates are considered to be most important from a network point of view. The dependencies of these values with input parameters like degree of replication, document popularity, actual cache hit rates, and error rates are highlighted. In order to determine the influence of different caching and replication strategies on the behavior of a single proxy server with respect to these values, trace-based simulations are used. Since the overall effects of such strate- gies can hardly be decided with this approach alone, a mathematical model has been developed to deal with their influence on the network as a whole. Together, this two-tiered approach permits us to propose quantita- tive assessments on the influence different caching and replication proposals (are going to) have on the Inter- net infrastructure.
We show how to prove ground confluence of term rewrite relations that areinduced by reductive systems of clausal rewrite rules. According to a well-knowncritical pair criterion it suffices for such systems to prove ground joinability ofa suitable set of 'critical clauses'. We outline how the latter can be done in asystematic fashion, using mathematical induction as a key concept of reasoning.
We present a new software architecture in which all concepts necessary to achieve fault tolerance can be added to an appli- cation automatically without any source code changes. As a case study, we consider the problem of providing a reliable service despite node failures by executing a group of replicat- ed servers. Replica creation and management as well as fail- ure detection and recovery are performed automatically by a separate fault tolerance layer (ft-layer) which is inserted be- tween the server application and the operating system kernel. The layer is invisible for the application since it provides the same functional interface as the operating system kernel, thus making the fault tolerance property of the service completely transparent for the application. A major advantage of our ar- chitecture is that the layer encapsulates both fault tolerance mechanisms and policies. This allows for maximum flexibility in the choice of appropriate methods for fault tolerance with- out any changes in the application code.
We describe a technique to make application programs fault tolerant. This techADnique is based on the concept of checkpointing from an active program to one ormore passive backup copies which serve as an abstraction of stable memory. Ifthe primary copy fails, one of the backup copies takes over and resumes processADing service requests. After each failure a new backup copy is created in order torestore the replication degree of the service. All mechanisms necessary to achieveand maintain fault tolerance can be added automatically to the code of a nonADfaulttolerant server, thus making fault tolerance completely transparent for the applicaADtion programmer.
Coordinating distributed processes, especially engineering and software design processes, has been a research topic for some time now. Several approaches have been published that aim at coordinating large projects in general, and large software development processes in specific. However, most of these approaches focus on the technical part of the design process and omit management activities like planning and scheduling the project, or monitoring it during execution. In this paper, we focus on coordinating the management activities that accompany the technical software design process. We state the requirements for a Software Engineering Environm ent (SEE) accommodating management, and we describe a possible architecture for such an SEE.
This paper describes the architecture and concept of operation of a Framework for Adaptive Process Modeling and Execution (FAME). The research addresses the absence of robust methods for supporting the software process management life cycle. FAME employs a novel, model-based approach in providing automated support for different activities in the software development life cycle including project definition, process design, process analysis, process enactment, process execution status monitoring, and execution status-triggered process redesign. FAME applications extend beyond the software development domain to areas such as agile manufacturing, project management, logistics planning, and business process reengineering.
In this paper we provide a semantical meta-theory that will support the development of higher-order calculi for automated theorem proving like the corresponding methodology has in first-order logic. To reach this goal, we establish classes of models that adequately characterize the existing theorem-proving calculi, that is, so that they are sound and complete to these calculi, and a standard methodology of abstract consistency methods (by providing the necessary model existence theorems) needed to analyze completeness of machine-oriented calculi.
In this paper we present an extensional higher-order resolution calculus that iscomplete relative to Henkin model semantics. The treatment of the extensionality princi-ples - necessary for the completeness result - by specialized (goal-directed) inference rulesis of practical applicability, as an implentation of the calculus in the Leo-System shows.Furthermore, we prove the long-standing conjecture, that it is sufficient to restrict the orderof primitive substitutions to the order of input formulae.
Collecting Experience on the Systematic Development of CBR Applications using the INRECA Methodology
(1999)
This paper presents an overview of the INRECA methodology for building and maintaining CBR applications. This methodology supports the collection and reuse of experience on the systematic development of CBR applications. It is based on the experience factory and the software process modeling approach from software engineering. CBR development experience is documented using software process models and stored in different levels of generality in a three-layered experience base. Up to now, experience from 9 industrial projects enacted by all INRECA II partners has been collected.
Complex problem solving can be substantially improved by the reuse of experience from previously solved problems. This requires that case libraries of successful problem solutions are transformed into problem solving knowledge with high utility, i.e. knowledge which causes high savings in search time, high application probability and low matching costs in a respective performance component. Planning can be improved by explanation-based learning (EBL) of abstract plans from detailed, successfully solved planning problems. Abstract plans, expressed in well-established terms of the domain, serve as useful problem decompositions which can drastically reduce the planning complexity. Abstractions which are valid for a class of planning cases rather than for a single case, ensure a successful application in a larger spectrum of new situations. The hierarchical organization of the learned shared abstractions causes low matching costs. The presented S-PABS procedure is an EBL-procedure in which abstraction, learning from multiple examples and hierarchical clustering are combined to automatically construct a hierarchy of shared abstract plans by analyzing concrete planning cases. A specific planning procedure has been designed to solve new planning problems guided by the knowledge learned by S-PABS. By allowing a feedback from this planning procedure to the learning component, the integrated system shows an increase in performance through past problem solving.
Although skeletal plan refinement is used in several planning systems, a procedure for the automatic acquisition of such high-level plans has not yet been developed. The proposed explanation- based knowledge acquisition procedure constructs a skeletal plan automatically from a sophisticated concrete planning case. The classification of that case into a well-described class of problems serves as an instrument for adjusting the applicability of the acquired skeletal plans to that class. The four phases of the proposed procedure are constituted as follows: In the first phase, the execution of the source plan is simulated, and explanations for the effects of the occurred operators are constructed. In the second phase, the generalization of these explanations is performed with respect to a criterion of operationality which specifies the vocabulary for defining abstract operators for the skeletal plan. The third phase, a dependency analysis of the resulting operator effects, unveils the interactions of the concrete plan which are substantial for the specified class. In the forth phase, the concept descriptions for the abstract operators of the skeletal plan are formed by collecting and normalizing the important constraints for each operation that were indicated by the dependencies. With this procedure sophisticated planning solutions from human experts can be generalized into skeletal plans and consequently be reused by a planning system in novel situations.
Abstraction is one of the most promising approaches to improve the performance of problem solvers. Abstraction by dropping sentences of a domain description - as used in most hierarchical planners - is known to be very representation dependent. To overcome these drawbacks, we propose a more general view of abstraction involving the change of representation language. We have developed a new abstraction methodology and a related sound and complete learning algorithm that allows the complete change of representation language of planning cases from concrete to abstract.
Recently, the use of abstraction in case-based reasoning (CBR) is getting more and more popular. The basic idea is to supply a CBR system with cases at many different levels of abstraction. When a new problem must be solved, one (or several) 'appropriate' concrete or abstract case are retrieved from the case base and the solution that the case contains is reused to derive a solution for the current problem, e.g. by filling in the details that a retrieved case at some higher level of abstraction does not contain. A major problem that occurs when using this approach is, that for a given new problem, usually several cases, e.g., from different levels of abstraction could be reused to solve the new problem. Choosing a wrong abstract case can slow down the problem solving process or even prevents the problem from being solved.
Hierachical planning can be improved by explanation-based learning (EBL) of abstract plans from detailed, successfully solved planning problems. Abstract plans, expressed in well-established terms of the domain, serve as useful problem decompositions which can drastically reduce the planning complexity. The learned plan abstraction must be valid for a class of planning cases rather than for a single case, to ensure their successful application in a larger spectrum of new situations. A hierarchical organization of the newly learned knowledge must be archieved to overcome the utility problem in EBL. This paper presents a new formal model of shared plan abstraction and the closely related explanation-based procedure S-PABS. Unlike other apporaches to plan abstraction, our model allows a total different terminology to be introduced at the abstract level. Finally, an unsupervised incremental procedure for constructing a hierachy of shared abstract plans is proposed, as a kind of concept formation over explanations.
This paper presents a brief overview of the INRECA-II methodology for building and maintaining CBR applications. It is based on the experience factory and the software process modeling approach from software engineering. CBR development and maintenance experience is documented using software process models and stored in a three-layered experience packet.
For defining attribute types to be used in the case representation, taxonomies occur quite often. The symbolic values at any node of the taxonomy tree are used as attribute values in a case or a query. A taxonomy type represents a relationship between the symbols through their position within the taxonomy-tree which expresses knowledge about the similarity between the symbols. This paper analyzes several situations in which taxonomies are used in different ways and proposes a systematic way of specifying local similarity measures for taxonomy types. The proposed similarity measures have a clear semantics and are easy to compute at runtime.
As the previous chapters of this book have shown, case-based reasoning is a technology that has been successfully applied to a large range of different tasks. Through all the different CBR projects, both basic research projects as well as industrial development projects, lots of knowledge and experience about how to build a CBR application has been collected. Today, there is already an increasing number of successful companies developing industrial CBR applications. In former days, these companies could develop their early pioneering CBR applications in an ad-hoc manner. The highly-skilled CBR expert of the company was able to manage these projects and to provide the developers with the required expertise.
Der Trend zu einer immer stärkeren Kopplung von Systemen bei gleichzeitiger Dezentralisierung durch Vernetzung hat dazu geführt, daß Computernutzern auf Wunsch enorme Datenmengen zur Verfügung stehen, die sich einer sinnvollen Bearbeitung durch den Nutzer allein völlig entziehen. Unterschiedliche Repräsentationsformalismen für Informationen, Mehrdeutigkeiten, Redundanz sowie eingeschränkte Verfügbarkeit sowohl von Informationen als auch von Rechenleistung machen konventionelle Suchverfahren unanwendbar. Stattdessen werden Suchverfahren und Programme benötigt, die sich intelligent an unterschiedliche Formalismen anpassen, ihre Handlungen ständig evaluieren und fähig sind, ihre Benutzer individuell zu unterstützen. Schlagwörter wie Knowbots, Search-Engines oder Data-Miningsind deshalb zur Zeit in aller Munde. Ein umfassendes Buch, das die hinter diesen und ähnlichen Schlagwörtern verborgenen Ideen und Konzepte präsentiert, existiert jedoch zur Zeit noch nicht. Dies war für uns die Motivation, das Thema "Intelligente Suche im Internet mit Lernenden Systemen" in einem Seminar zu behandeln. Wir haben damit ein Forschungsgebiet aufgegriffen, das sowohl für alle am LSA beteiligten Gruppen von Interesse ist, aber darüber hinaus aktuell von vielen Seiten aufmerksam beobachtet wird. Daher haben wir uns entschlossen, die Ausarbeitungen, die im Rahmen dieses Seminars von den TeilmehmerInnen erstellt wurden, durch den vorliegenden Bericht einer breiteren Öffentlichkeit zugänglich zu machen.
Bei der Erstellung komplexer Software spielt die Wiederverwendung vorhandener Programmbestandteile eine besonders grosse Rolle, da hierdurch sowohl die Software-Qualität gesteigert, als auch der gesamte Erstellungsund Wartungsaufwand erheblich reduziert werden kann. In jüngster Zeit gewinnen objektorientierte Programmiersprachen zunehmend an Bedeutung, da die Wiederverwendung hierbei bereits durch Sprachkonzepte wie z.B. Vererbung und Polymorphie unterstützt wird. Weiterhin besteht jedoch das Problem, zur Wiederverwendung geeignete Programmbestandteile aufzufinden. Ziel dieser Arbeit ist es herauszufinden, inwieweit fallbasiertes Schliessen nach dem aktuellen Stand der Kunst die Wiederverwendung objektorientierter Software unt erstützen kann. Hierzu wurde eine entsprechende Anwendung prototypisch auf der Basis des INRECA-Systems entwickelt. Durch ausgewählte Testsituationen wurden Erfahrungen mit diesem Prototyp gesammelt und systematisch ausgewertet.
Planning means constructing a course of actions to achieve a specified set of goals when starting from an initial situation. For example, determining a sequence of actions (a plan) for transporting goods from an initial location to some destination is a typical planning problem in the transportation domain. Many planning problems are of practical interest.
Case-based problem solving can be significantly improved by applying domain knowledge (in opposition to problem solving knowledge), which can be acquired with reasonable effort, to derive explanations of the correctness of a case. Such explanations, constructed on several levels of abstraction, can be employed as the basis for similarity assessment as well as for adaptation by solution refinement. The general approach for explanation-based similarity can be applied to different real world problem solving tasks such as diagnosis and planning in technical areas. This paper presents the general idea as well as the two specific, completely implemented realizations for a diagnosis and a planning task.
Object-oriented case representations require approaches for similarity assessment that allow to compare two differently structured objects, in particular, objects belonging to different object classes. Currently, such similarity measures are developed more or less in an ad-hoc fashion. It is mostly unclear, how the structure of an object-oriented case model, e.g., the class hierarchy, influences similarity assessment. Intuitively, it is obvious that the class hierarchy contains knowledge about the similarity of the objects. However, how this knowledge relates to the knowledge that could be represented in similarity measures is not obvious at all. This paper analyzes several situations in which class hierarchies are used in different ways for case modeling and proposes a systematic way of specifying similarity measures for comparing arbitrary objects from the hierarchy. The proposed similarity measures have a clear semantics and are computationally inexpensive to compute at run-time.
This paper addresses the role of abstraction in case-based reasoning. We develop a general framework for reusing cases at several levels of abstraction, which is particularly suited for describing and analyzing existing and designing new approaches of this kind. We show that in synthetic tasks (e.g. configuration, design, and planning), abstraction can be successfully used to improve the efficiency of similarity assessment, retrieval, and adaptation. Furthermore, a case-based planning system, called Paris, is described and analyzed in detail using this framework. An empirical study done with Paris demonstrates significant advantages concerning retrieval and adaptation efficiency as well as flexibility of adaptation. Finally, we show how other approaches from the literature can be classified according to the developed framework.
This paper is to present a new algorithm, called KNNcost, for learning feature weights for CBR systems used for classification. Unlike algorithms known so far, KNNcost considers the profits of a correct and the cost of a wrong decision. The need for this algorithm is motivated from two real-world applications, where cost and profits of decisions play a major role. We introduce a representation of accuracy, cost and profits of decisions and define the decision cost of a classification system. To compare accuracy optimization with cost optimization, we tested KNNacc against KNNcost. The first one optimizes classification accuracy with a conjugate gradient algorithm. The second one optimizes the decision cost of the CBR system, respecting cost and profits of the classifications. We present experiments with these two algorithms in a real application to demonstrate the usefulness of our approach.
Paris (Plan Abstraction and Refinement in an Integrated System) [4, 2] is a domain independent case-based planning system which allows the flexible reuse of planning cases by abstraction and refinement. This approach is mainly inspired by the observation that reuse of plans must not be restricted to a single description level. In domains with a high variation in the problems, the reuse of past solutions must be achieved at various levels of abstraction.
Abstraction is one of the most promising approaches to improve the performance of problem solvers. In several domains abstraction by dropping sentences of a domain description - as used in most hierarchical planners - has proven useful. In this paper we present examples which illustrate significant drawbacks of abstraction by dropping sentences. To overcome these drawbacks, we propose a more general view of abstraction involving the change of representation language. We have developed a new abstraction methodology and a related sound and complete learning algorithm that allows the complete change of representation language of planning cases from concrete to abstract. However, to achieve a powerful change of the representation language, the abstract language itself as well as rules which describe admissible ways of abstracting states must be provided in the domain model. This new abstraction approach is the core of PARIS (Plan Abstraction and Refinement in an Integrated System), a system in which abstract planning cases are automatically learned from given concrete cases. An empirical study in the domain of process planning in mechanical engineering shows significant advantages of the proposed reasoning from abstract cases over classical hierarchical planning.^
Lernen von Abstraktionshierarchien zur Optimierung der Auswahl von maschinell abstrahierten Plänen
(1994)
Mit Hilfe von "Multistrategy" Ansätzen, die erklärungsbasiertes und induktives Lernen integrieren, ist es möglich, die Performanz von Planungssystemen signifikant zu verbessern. Dabei können gelöste Planungsprobleme zunächst mit einem wissensintensiven Verfahren abstrahiert und generalisiert werden. Durch den in diesem Beitrag im Vordergrund stehenden induktiven inkrementellen Lernalgorithmus ist es dann weiterhin möglich, die Gesamtheit des deduktiv generierten Wissens in einer Abstraktionshierarchie anzuordnen. Dabei wird die, im allgemeinen unentscheidbare, "spezieller-als-Relation" zwischen generalisierten Plänen, induktiv aus den gegebenen Planungsfällen gelernt. Diese Abstraktionshierarchie dient dann zur Klassifikation neuer Problemstellungen und damit zur Bestimmung einer speziellsten anwendbaren abstrakten Problemlösung.
In this paper, we propose the PARIS approach for improving complex problem solving by learning from previous cases. In this approach, abstract planning cases are learned from given concrete cases. For this purpose, we have developed a new abstraction methodology that allows to completely change the representation language of a planning case, when the concrete and abstract languages are given by the user. Furthermore, we present a learning algorithm which is correct and complete with respect to the introduced model. An empirical study in the domain of process planning in mechanical engineering shows significant improvements in planning efficiency through learning abstract cases while an explanation-based learning method only causes a very slight improvement.
Although several systematic analyses of existing approaches to adaptation have been published recently, a general formal adaptation framework is still missing. This paper presents a step into the direction of developing such a formal model of transformational adaptation. The model is based on the notion of the quality of a solution to a problem, while quality is meant in a more general sense and can also denote some kind of appropriateness, utility, or degree of correctness. Adaptation knowledge is then defined in terms of functions transforming one case into a successor case. The notion of quality provides us with a semantics for adaptation knowledge and allows us to define terms like soundness, correctness and completeness. In this view, adaptation (and even the whole CBR process) appears to be a special instance of an optimization problem.
Case-based problem solving can be significantly improved by applying domain knowledge (in opposition to problem solving knowledge), which can be acquired with reasonable effort, to derive explanations of the correctness of a case. Such explanations, constructed on several levels of abstraction, can be employed as the basis for similarity assessment as well as for adaptation by solution refinement. The general approach for explanation-based similarity can be applied to different real world problem solving tasks such as diagnosis and planning in technical areas. This paper presents the general idea as well as the two specific, completely implemented realizations for a diagnosis and a planning task.
When problems are solved through reasoning from cases, the primary kind of knowledge is contained in the specific cases which are stored in the case base. However, in many situations additional background-knowledge is required to cope with the requirements of an application. We describe an approach to integrate such general knowledge into the reasoning process in a way that it complements the knowledge contained in the cases. This general knowledge itself is not sufficient to perform any kind of model-based problem solving, but it is required to interpret the available cases appropriately. Background knowledge is expressed by two different kinds of rules that both must be formalized by the knowledge engineer: Completion rules describe how to infer additional features out of known features of an old case or the current query case. Adaptation rules describe how an old case can be adapted to fit the current query. This paper shows how these kinds of rules can be integrated into an object-oriented case representation.
This paper motivates the necessity for support for negotiation during Sales Support on the Internet within Case-Based Reasoning solutions. Different negotiation approaches are discussed and a general model of the sales process is presented. Further, the tradition al CBR-cycle is modified in such a way that iterative retrieval during a CBR consulting session is covered by the new model. Several gen eral characteristics of negotiation are described and a case study is shown where preliminary approaches are used to negotiate with a cu stomer about his demands and available products in a 'CBR-based' Electronic Commerce solution.
Automata-Theoretic vs. Property-Oriented Approaches for the Detection of Feature Interactions in IN
(1999)
The feature interaction problem in Intelligent Networks obstructs more and morethe rapid introduction of new features. Detecting such feature interactions turns out to be a big problem. The size of the systems and the sheer computational com-plexity prevents the system developer from checking manually any feature against any other feature. We give an overview on current (verification) approaches and categorize them into property-oriented and automata-theoretic approaches. A comparisonturns out that each approach complements the other in a certain sense. We proposeto apply both approaches together in order to solve the feature interaction problem.
The feature interaction problem in telecommunications systems increasingly ob-structs the evolution of such systems. We develop formal detection criteria whichrender a necessary (but less than sufficient) condition for feature interactions. It can be checked mechanically and points out all potentially critical spots. Thesehave to be analysed manually. The resulting resolution decisions are incorporatedformally. Some prototype tool support is already available. A prerequisite forformal criteria is a formal definition of the problem. Since the notions of featureand feature interaction are often used in a rather fuzzy way, we attempt a formaldefinition first and discuss which aspects can be included in a formalization (andtherefore in a detection method). This paper describes ongoing work.
In nebenläufigen Systemen erleichtert das Konzept der Atomarität vonOperationen, konkurrierende Zugriffe in größere, leichter beherrschbareAbschnitte zu unterteilen. Wenn wir aber Spezifikationen in der forma-len Beschreibungstechnik Estelle betrachten, erweist es sich, daß es un-ter bestimmten Umständen schwierig ist, die Atomarität der sogenanntenTransitionen bei Implementationen exakt einzuhalten, obwohl diese Ato-marität eine konzeptuelle Grundlage der Semantik von Estelle ist. Es wirdaufgezeigt, wie trotzdem sowohl korrekte als auch effiziente nebenläufigeImplementationen erreicht werden können. Schließlich wird darauf hinge-wiesen, daß die das Problem auslösenden Aktionen oft vom Spezifiziererleicht von vorneherein vermieden werden können; und dies gilt auch überden Kontext von Estelle hinaus.
The feature interaction problem in telecommunications systems increasingly obstructsthe evolution of such systems. We develop formal detection criteria which render anecessary (but less than sufficient) condition for feature interactions. It can be checkedmechanically and points out all potentially critical spots. These have to be analyzedmanually. The resulting resolution decisions are incorporated formally. Some prototypetool support is already available. A prerequisite for formal criteria is a formal definitionof the problem. Since the notions of feature and feature interaction are often used in arather fuzzy way, we attempt a formal definition first and discuss which aspects can beincluded in a formalization (and therefore in a detection method). This paper describeson-going work.
A Case Study on Specifikation,Detection and Resolution of IN Feature Interactions with Estelle
(1994)
We present an approach for the treatment of Feature Interactions in Intelligent Networks. The approach is based on the formal description technique Estelle and consists of three steps. For the first step, a specification style supporting the integration of additional features into a basic service is introduced . As a result, feature integration is achieved by adding specification text, i.e . on a purely syntactical level. The second step is the detection of feature interactions resulting from the integration of additional features. A formal criterion is given that can be used for the automatic detection of a particular class of feature interactions. In the third step, previously detected feature interactions are resolved. An algorithm has been devised that allows the automatical incorporation of high-level design decisions into the formal specification. The presented approach is applied to the Basic Call Service and several supplementary interacting features.
AbstractOne main purpose for the use of formal description techniques (FDTs) is formal reasoningand verification. This requires a formal calculus and a suitable formal semantics of theFDT. In this paper, we discuss the basic verification requirements for Estelle, and howthey can be supported by existing calculi. This leads us to the redefinition of the stanADdard Estelle semantics using Lamport's temporal logic of actions and Dijkstra's predicatetransformers.
In this report we give an overview of the development of our new Waldmeisterprover for equational theories. We elaborate a systematic stepwise design process, startingwith the inference system for unfailing Knuth - Bendix completion and ending up with animplementation which avoids the main diseases today's provers suffer from: overindulgencein time and space.Our design process is based on a logical three - level system model consisting of basicoperations for inference step execution, aggregated inference machine, and overall controlstrategy. Careful analysis of the inference system for unfailing completion has revealed thecrucial points responsible for time and space consumption. For the low level of our model,we introduce specialized data structures and algorithms speeding up the running system andcutting it down in size - both by one order of magnitude compared with standard techniques.Flexible control of the mid - level aggregation inside the resulting prover is made possible by acorresponding set of parameters. Experimental analysis shows that this flexibility is a pointof high importance. We go on with some implementation guidelines we have found valuablein the field of deduction.The resulting new prover shows that our design approach is promising. We compare oursystem's throughput with that of an established system and finally demonstrate how twovery hard problems could be solved by Waldmeister.
We present an empirical study of mathematical proofs by diagonalization, the aim istheir mechanization based on proof planning techniques. We show that these proofs canbe constructed according to a strategy that (i) finds an indexing relation, (ii) constructsa diagonal element, and (iii) makes the implicit contradiction of the diagonal elementexplicit. Moreover we suggest how diagonal elements can be represented.
This report is a first attempt of formalizing the diagonalization proof technique.We give a strategy how to systematically construct diagonalization proofs: (i) findingan indexing relation, (ii) constructing a diagonal element, and (iii) making the implicitcontradiction of the diagonal element explicit. We suggest a declarative representationof the strategy and describe how it can be realized in a proof planning environment.
This report presents a methodology to guide equational reasoningin a goal directed way. Suggested by rippling methods developed inthe field of inductive theorem proving we use attributes of terms andheuristics to determine bridge lemmas, i.e. lemmas which have tobe used during the proof of the theorem. Once we have found sucha bridge lemma we use the techniques of difference unification andrippling to enable its use.
In the recent years a form of software development that was previously dismissed as too ad-hoc and chaotic for serious projects has suddenly taken the front stage. With products such as Apache, Linux, Perl, and others, open-source software has emerged as a viable alternative to traditional approaches to software development. With its globally distributed developer force and extremely rapid code evolution, open source is arguably the extreme in "virtual software projects" [1], and exemplifies many of the advantages and challenges of distributed software development.
This paper describes the design and implementation of a process support system (PROSYT), which is intended to provide guidance in performing business processes and cooperation among people over a local or geographically distributed architecture. In particular, it can be used as a Process-centered Software Engineering Environment (PSEE) to support distributed software development. Our main purpose is to describe how complex applications of this kind can be developed systematically. In particular, how the requirements of high flexibility, reconfigurability, scalability, and efficiency demanded by these applications can be met through appropriate design choices.
CORBA Lacks Venom
(1999)
Distributed objects bring to distributed computing such desirable properties of modularisation, abstraction and reuse easing the burden of development and maintenance by diminishing the gap between implementation and real-world objects. Distributed objects, however, need a consistent framework in which inter-object communication may take place. The Common Object Request Broker Architecture (CORBA) is a distributed object standard. CORBA's primary protocol is the Internet Interoperable Object Protocol limited to blocked synchronous remote procedure calls, over TCP/IP which is inappropriate for systems requiring timely guarantees.
There are two general approaches to providing for isochronous streams in the current Internet. The first approach is the resource reservation approach through protocols such as RSVP, or ATM technology. This provides bandwidth guarantees, however, it also requires significant upgrading of resources in the underlying network. The other common approach is adaptive rate control where the end-system has control of its rate according to feedback from the client population. This approach cannot guarantee timely delivery and raises some scaling questions, however a properly implemented scheme does improve quality and it requires no changes to the underlying IP network. Hence, there exists a dichotomy of requirements ; 1. To cater for reservation protocols or 'hooks' for future reservation components, and 2. To provide an architecture which provides an application controlled QoS scheme, which scales to the size of the current Internet in a best- effort architecture.
In recent years the demand on business process modelling (BPM) became apparent in many different communities, e.g. information systems engineering, requirements engineering [KiB94], software engineering and knowledge engineering (e.g. [BrV94], [SWH+94]). This suggests to aim at a unifying view on business process modelling in all these disciplines. To achieve the business goals some problems which obstruct these goals must be solved. This can be done either by restructuring the business process, by application of standard software, or by developing individual software components such as knowledge based systems (KBSs). To be able to model business goals and to analyse problems occurring during the business processes these processes including organisational structures and activities have to be modelled. This is also true when building a KBS in an enterprise environment. Because the KBS is only a small part of the whole business organisation, it must be embedded into or at least linked to all relevant business processes, i.e. it should not be a stand-alone solution. For this purpose we extend the MIKE approach [AFS96] in the BMBF project WORKS (Work Oriented Design of Knowledge Systems) by offering business models for modelling relevant aspects of an enterprise. To be able to define an integrated framework with other possibilties to improve an enterprise (e.g. information systems engineering) we determine the standard views of an enterprise. Next we define the views, that are necessary for developing a KBS.
A large set of criteria to evaluate formal methods for reactive systems is presented. To make this set more comprehensible, it is structured according to a Concept-Model of formal methods. It is made clear that it is necessary to make the catalogue more specific before applying it. Some of the steps needed to do so are explained. As an example the catalogue is applied within the context of the application domain building automation systems to three different formal methods: SDL, statecharts, and a temporallogic.
A combination of a state-based formalism and a temporal logic is proposed to get an expressive language for various descriptions of reactive systems. Thereby it is possible to use a model as well as a property oriented specification style in one description. The descriptions considered here are those of the environment, the specification, and the design of a reactive system. It is possible to express e.g. the requirements of a reactive system by states and transitions between them together with further temporal formulas restricting the behaviors of the statecharts. It is shown, how this combined formalism can be used: The specification of a small example is given and a designed controller is proven correct with respect to this specification. The combination of the langugages is based on giving a temporal semantics of a state-based formalism (statecharts) using a temporal logic (TLA).
There are well known examples of monoids in literature which do not admit a finite andcanonical presentation by a semi-Thue system over a fixed alphabet, not even over an arbi-trary alphabet. We introduce conditional Thue and semi-Thue systems similar to conditionalterm rewriting systems as defined by Kaplan. Using these conditional semi-Thue systems wegive finite and canonical presentations of the examples mentioned above. Furthermore weshow, that each finitely generated monoid with decidable word problem is embeddable in amonoid which has a finite canonical conditional presentation.
Representations of activities dealing with the development or maintenance of software are called software process models. Process models allow for communication, reasoning, guidance, improvement, and automation. Two approaches for building, instantiating, and managing processes, namely CoMo-Kit and MVP-E, are combined to build a more powerful one. CoMo-Kit is based on AI/KE technology; it was developed for supporting complex design processes and is not specialized to software development processes. MVP-E is a process-sensitive software engineering environment for modeling and analyzing software development processes, and guides software developers. Additionally, it provides services to establish and run measurement programmes in software organizations. Because both approaches were developed completely independently major integration efforts are to be made to combine their both advantages. This paper concentrates on the resulting language concepts and their operationalization necessary for building automated process support.
We present an approach to prove several theorems in slightly different axiomsystems simultaneously. We represent the different problems as a taxonomy, i.e.a tree in which each node inherits all knowledge of its predecessors, and solve theproblems using inference steps on rules and equations with simple constraints,i.e. words identifying nodes in the taxonomy. We demonstrate that a substantialgain can be achieved by using taxonomic constraints, not only by avoiding therepetition of inference steps in the different problems but also by achieving runtimes that are much shorter than the accumulated run times when proving eachproblem separately.
We present a concept for an automated theorem prover that employs a searchcontrol based on ideas from several areas of artificial intelligence (AI). The combi-nation of case-based reasoning, several similarity concepts, a cooperation conceptof distributed AI and reactive planning enables a system using our concept tolearn form previous successful proof attempts. In a kind of bootstrapping processeasy problems are used to solve more and more complicated ones.We provide case studies from two domains of interest in pure equationaltheorem proving taken from the TPTP library. These case studies show thatan instantiation of our architecture achieves a high grade of automation andoutperforms state-of-the-art conventional theorem provers.
We present an approach to learning cooperative behavior of agents. Our ap-proach is based on classifying situations with the help of the nearest-neighborrule. In this context, learning amounts to evolving a set of good prototypical sit-uations. With each prototypical situation an action is associated that should beexecuted in that situation. A set of prototypical situation/action pairs togetherwith the nearest-neighbor rule represent the behavior of an agent.We demonstrate the utility of our approach in the light of variants of thewell-known pursuit game. To this end, we present a classification of variantsof the pursuit game, and we report on the results of our approach obtained forvariants regarding several aspects of the classification. A first implementationof our approach that utilizes a genetic algorithm to conduct the search for a setof suitable prototypical situation/action pairs was able to handle many differentvariants.
The team work method is a concept for distributing automated theoremprovers and so to activate several experts to work on a given problem. We haveimplemented this for pure equational logic using the unfailing KnuthADBendixcompletion procedure as basic prover. In this paper we present three classes ofexperts working in a goal oriented fashion. In general, goal oriented experts perADform their job "unfair" and so are often unable to solve a given problem alone.However, as a team member in the team work method they perform highly effiADcient, even in comparison with such respected provers as Otter 3.0 or REVEAL,as we demonstrate by examples, some of which can only be proved using teamwork.The reason for these achievements results from the fact that the team workmethod forces the experts to compete for a while and then to cooperate by exADchanging their best results. This allows one to collect "good" intermediate resultsand to forget "useless" ones. Completion based proof methods are frequently reADgarded to have the disadvantage of being not goal oriented. We believe that ourapproach overcomes this disadvantage to a large extend.
We present an overview of various learning techniques used in automated theorem provers. We characterize the main problems arising in this context and classify the solutions to these problems from published approaches. We analyze the suitability of several combinations of solutions for different approaches to theorem proving and place these combinations in a spectrum ranging from provers using very specialized learning approaches to optimally adapt to a small class of proof problems, to provers that learn more general kinds of knowledge, resulting in systems that are less efficient in special cases but show improved performance for a wide range of problems. Finally, we suggest combinations of solutions for various proof philosophies.
This paper presents a new way to use planning in automated theorem provingby means of distribution. To overcome the problem that often subtasks fora proof problem can not be detected a priori (which prevents the use of theknown planning and distribution techniques) we use a team of experts that workindependently with different heuristics on the problem. After a certain amount oftime referees judge their results using the impact of the results on the behaviourof the expert and a supervisor combines the selected results to a new startingpoint.This supervisor also selects the experts that can work on the problem inthe next round. This selection is a reactive planning task. We outline whichinformation the supervisor can use to fulfill this task and how this informationis processed to result in a plan or to revise a plan. We also show that the useof planning for the assignment of experts to the team allows the system to solvemany different examples in an acceptable time with the same start configurationand without any consultation of the user.Plans are always subject to changeShin'a'in proverb
We present a distributed system, Dott, for approximately solving the Trav-eling Salesman Problem (TSP) based on the Teamwork method. So-calledexperts and specialists work independently and in parallel for given time pe-riods. For TSP, specialists are tour construction algorithms and experts usemodified genetic algorithms in which after each application of a genetic operatorthe resulting tour is locally optimized before it is added to the population. Aftera given time period the work of each expert and specialist is judged by a referee.A new start population, including selected individuals from each expert and spe-cialist, is generated by the supervisor, based on the judgments of the referees.Our system is able to find better tours than each of the experts or specialistsworking alone. Also results comparable to those of single runs can be found muchfaster by a team.
Automatic proof systems are becoming more and more powerful.However, the proofs generated by these systems are not met withwide acceptance, because they are presented in a way inappropriatefor human understanding.In this paper we pursue two different, but related, aims. First wedescribe methods to structure and transform equational proofs in away that they conform to human reading conventions. We developalgorithms to impose a hierarchical structure on proof protocols fromcompletion based proof systems and to generate equational chainsfrom them.Our second aim is to demonstrate the difficulties of obtaining suchprotocols from distributed proof systems and to present our solutionto these problems for provers using the TEAMWORK method. Wealso show that proof systems using this method can give considerablehelp in structuring the proof listing in a way analogous to humanbehaviour.In addition to theoretical results we also include descriptions onalgorithms, implementation notes, examples and data on a variety ofexamples.
Multi-User Dimensions (MUDs) [3], and their Object-Oriented versions (MOOs) [6], are geographically distributed, programmable client-server systems that support the cooperation of multiple users according to the virtual environment metaphor. In this metaphor, users are allowed to concurrently navigate in a set of "virtual" rooms. Rooms are interconnected through doors and may contain objects. Users are allowed to explore the contents of rooms, create and manipulate objects, and contact other users visiting the same room.
This paper investigates the suitability of the mobile agents approach to the problem of integrating a collection of local DBMS into a single heterogeneous large-scale distributed DBMS. The paper proposes a model of distributed transactions as a set of mobile agents and presents the relevant execution semantics. In addition, the mechanisms which are needed to guarantee the ACID properties in the considered environment are discussed.
In this paper the autonomous mobile vehicle MOBOT-IV is presented, which is capable of exploring an indoor-environment while building up an internal representation of its world. This internal model is used for the navigation of the vehicle during and after the exploration phase. In contrast to methods, which use a grid based or line based environment representation, in the approach presented in this paper, local sector maps are the basic data structure of the world model. This paper describes the method of the view-point-planning for map building, the use of this map for navigation and the method of external position estimation including the hand- ling of an position error in a moving real-time system.
Auf KLUEDO, dem Kaiserslauterer uniweiten elektronischen Dokumentenserver, können Angehörige der Universität Kaiserslautern wissenschaftliche Dokumente in elektronischer Form im Internet und damit weltweit veröffentlichen. Der Dokumentenserver entstand auf Initiative der Fachbereiche und der Universitätsbibliothek Kaiserslautern im Rahmen des vom Bundesministerium für Bildung und Forschung (BMBF) geförderten GLOBAL INFO - Vorprojektes. Hierbei basiert der Dokumentenserver stellenweise auf dem (während des MathNet-Projektes des deutschen Forschungsnetzes (DFN) und des MathBibNet-Projektes der deutschen Forschungsgemeinschaft (DFG) aufgebauten) Mathematik-Preprintserver der Universität Kaiserslautern. Dieser Artikel umreißt die Aspekte, die hinter der Entwicklung des Dokumentenservers in der vorliegenden Form gestanden haben und gibt einen groben Überblick über die Systemarchitektur. Detailinformationen und eine Beschreibung des Systems findet man in meiner Arbeit Propadeutik metadatenbasierter Publikationsserver: Ontologie und konkordante Implementierung.
Komprimierungsverfahren
(1999)
Bedingt durch das Wachstum von Informationsnachfrage und -angebot werden effizientere Wege zur Repräsentation von Informationen aller Art benötigt. Dies kann sowohl durch Assimilation und Optimierung der gewählten Datenstruktur und ihrer Repräsentation als auch (additiv) durch Komprimierung derselbigen erreicht werden. Diese Ausarbeitung soll in pragmatischer Art und Weise in das Themengebiet der Komprimierung einführen. Vorgestellt werden insgesamt 3 Stellvertreter aus unterschiedlichen Bereichen : Komprimierung von Texten mittels Huffman-Code, Komprimierung von Bitlisten mittels Laufkomprimierung (RLE-Komprimierung), Komprimierung von - auf dem RGB-Farbmodell basierenden - Grafiken mittels eines eigenen Verfahrens. Während die ersten beiden Verfahren Vertreter verlustfreier Komprimierung sind, ist das Dritte ein Vertreter der verlustbehafteten Komprimierung. Die vorgestellten Verfahren werden zur Arrondierung an konkreten Beispielen eingeübt und schließlich sogar in der Programmiersprache Pascal implementiert. Die konkrete Realisation in einer gegebenen Programmiersprache birgt kanonischerweise die Gefahr, den Blick für das Wesentliche zu verlieren. Deshalb wurde bei der Erstellung dieser Ausarbeitung (im speziellen der Programmieraufgaben) akribisch auf Abstrahierung unnötiger Details geachtet.
Das System ART (ASF RRL Translation) stellt im wesentlichen eine Umgebung dar,in welcher die Modularisierbarkeit von Beweisen (Induktionsbeweisen über Gleichungs-spezifikationen) untersucht werden kann. Es wurde die bereits bestehende Spezifikati-onsprache ASF (siehe [BeHeKl89]), in welcher modularisierte Spezifikationen möglichsind, so erweitert, daß zusätzlich auch Beweisaufgaben spezifiziert werden können. Imfolgenden wird diese erweiterte Spezifikationsprache auch ASF genannt. Als Bewei-ser für die Beweisaufgaben einer Spezifikation wurde RRL (siehe [KaZh89]) gewählt.RRL kann sowohl Kommandos aus einem File abarbeiten, wie auch Sitzungsprotokolleanfertigen, mit deren Hilfe sich die Beweisverläufe und Benutzereingaben der entspre-chenden RRL-Sitzung rekonstruieren lassen. In ART kann nun eine ASF-Spezifikation,die Beweisaufgaben umfassen kann, in ein File übersetzt werden, welches von RRLabgearbeitet werden kann. Dies wird im folgenden kurz mit 'Übersetzung von ASF nach RRL' bezeichnet. Bei der Abarbeitung eines solchen Files wird von RRL ein Sit-zungsprotokoll angelegt. ART kann dieses Sitzungsprotokoll dazu heranziehen, neueErgebnisse, wie etwa den erfolgreichen Beweis einer Beweisaufgabe, zu ermitteln, umdiese Ergebnisse der ursprüngliche Spezifikation hinzuzufügen. Dies wird im folgendenkurz mit 'Rückübersetzung von RRL nach ASF' bezeichnet. Im Kern besteht ART alsoaus einer Komponente zur Übersetzung von ASF nach RRL und aus einer Komponentezur Rückübersetzung von RRL nach ASF.
This paper provides a description of PLATIN. With PLATIN we present an imple-mented system for planning inductive theorem proofs in equational theories that arebased on rewrite methods. We provide a survey of the underlying architecture ofPLATIN and then concentrate on details and experiences of the current implementa-tion.