## Fachbereich Informatik

### Refine

#### Year of publication

- 1996 (50) (remove)

#### Document Type

- Preprint (27)
- Report (9)
- Article (7)
- Master's Thesis (7)

#### Keywords

- AG-RESY (4)
- COMOKIT (4)
- Case-Based Reasoning (3)
- CoMo-Kit (3)
- PARO (3)
- Fallbasiertes Planen (2)
- SKALP (2)
- case-based planning (2)
- Abstraction (1)
- Fallbasiertes Schliessen (1)
- General Knowledge (1)
- Genetic Algorithm (1)
- Instance-based Learning (1)
- Knowledge-based Techniques (1)
- LOADBAL (1)
- Nearest-Neighbor Classification (1)
- Object-OrientedCase Representation (1)
- PLAN Abstraction (1)
- Prozessmodellen (1)
- ReasoningSystems (1)
- Software Process Support (1)
- Software-Entwicklung (1)
- Sprachen (1)
- artificial neural networks (1)
- case-based reasoning (1)
- complex System Development (1)
- conceptual design (1)
- constraint-based reasoning (1)
- description of reactive systems (1)
- distributed computing (1)
- hypercubes (1)
- load balancing (1)
- load sharing (1)
- mobile robots (1)
- navigation (1)
- parallel algorithms (1)
- planning (1)
- rekursiv aufzählbare Sprachfamilien (1)
- rings (1)
- rule-based reasoning (1)
- search-space-problem (1)
- self-organization (1)
- state-based formalism (1)
- temporal logic (1)
- tori (1)
- world-modelling (1)

One of the many features needed to support the activities of autonomous systems is the ability of motion planning. It enables robots to move in their environment securely and to accomplish given tasks. Unfortunately, the control loop comprising sensing, planning, and acting has not yet been closed for robots in dynamic environments. One reason involves the long execution times of the motion planning component. A solution for this problem is offered by the use of highly computational parallelism. Thus, an important task is the parallelization of existing motion planning algorithms for robots so that they are suitable for highly computational parallelism. In several cases, completely new algorithms have to be designed, so that a parallelization is feasible. In this survey, we review recent approaches to motion planning using parallel computation.

We present an approach to systematically describing case-based reasoning systems bydifferent kinds of criteria. One main requirement was the practical relevance of these criteria and their usability for real-life applications. We report on the results we achieved from a case study carried out in the INRECA1 Esprit project.

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).

Complete Eager Replay
(1996)

We present an algorithm for completely replaying previous problem solving experiences for plan-space planners. In our approach not only the solution trace is replayed, but also the explanations of failed attempts made by the first-principle planner. In this way, the capability of refitting previous solutions into new problems is improved.

In recent years, Smolyak quadrature rules (also called hyperbolic cross points or sparse grids) have gained interest as a possible competitor to number theoretic quadratures for high dimensional problems. A standard way of comparing the quality of multivariate quadrature formulas
consists in computing their \(L_2\)-discrepancy. Especially for larger dimensions, such computations are a highly complex task. In this paper we develop a fast recursive algorithm for computing the \(L_2\)-discrepancy (and related quality measures) of general Smolyak quadratures. We carry out numerical comparisons between the discrepancies of certain Smolyak rules, Hammersley and Monte Carlo sequences.

A notion of discrepancy is introduced, which represents the integration error on spaces of \(r\)-smooth periodic functions. It generalizes the diaphony and constitutes a periodic counterpart to the classical \(L_2\)-discrepancy as weil as \(r\)-smooth versions of it introduced recently by Paskov [Pas93]. Based on previous work [FH96], we develop an efficient algorithm for computing periodic discrepancies for quadrature formulas possessing certain tensor product structures, in particular, for Smolyak quadrature rules (also called sparse grid methods). Furthermore, fast algorithms of computing periodic discrepancies for lattice rules can easily be derived from well-known properties of lattices. On this basis we carry out numerical comparisons of discrepancies between Smolyak and lattice rules.

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.

In this paper we describe how explicit models of software or knowledge engineering processes can be used to guide and control the distributed development of complex systems. The paper focuses on techniques which automatically infer dependencies between decisions from a process model and methods which allow to integrate planning and execution steps. Managing dependencies between decisions is a basis for improving the traceability of develop- ment processes. Switching between planning and execution of subprocesses is an inherent need in the development of complex systems. The paper concludes with a description of the CoMo-Kit system which implements the technolo- gies mentioned above and which uses WWW technology to coordinate development processes. An on-line demonstration of the system can be found via the CoMo-Kit homepage:

Fallbasiertes Schliessen (engl.: Case-based Reasoning) hat in den vergangenen Jahren zunehmende Bedeutung für den praktischen Einsatz in realen Anwendungsbereichen erlangt. In dieser Arbeit werden zunächst die allgemeine Vorgehensweise und die verschiedenen Teilaufgaben des fallbasierten Schliessens vorgestellt. Anschliessend wird auf die charakteristischen Eigenschaften eines Anwendungsbereiches eingegangen und an der konkreten Aufgabe der Kreditwürdigkeitsprüfung die Realisierung eines fallbasierten Ansatzes in der Finanzwelt beschrieben.