We investigate in how far interpolation mechanisms based on the nearest-neighbor rule (NNR) can support cancer research. The main objective is to usethe NNR to predict the likelihood of tumorigenesis based on given risk factors.By using a genetic algorithm to optimize the parameters of the nearest-neighbourprediction, the performance of this interpolation method can be improved sub-stantially. Furthermore, it is possible to detect risk factors which are hardly ornot relevant to tumorigenesis. Our preliminary studies demonstrate that NNR-based interpolation is a simple tool that nevertheless has enough potential to beseriously considered for cancer research or related research.
We present a general framework for developing search heuristics for au-tomated theorem provers. This framework allows for the construction ofheuristics that are on the one hand able to replay (parts of) a given prooffound in the past but are on the other hand flexible enough to deviate fromthe given proof path in order to solve similar proof problems. We substanti-ate the abstract framework by the presentation of three distinct techniquesfor learning appropriate search heuristics based on soADcalled features. Wedemonstrate the usefulness of these techniques in the area of equational de-duction. Comparisons with the renowned theorem prover Otter validatethe applicability and strength of our approach.
Retrieving multiple cases is supposed to be an adequate retrieval strategy for guiding partial-order planners because of the recognized flexibility of these planners to interleave steps in the plans. Cases are combined by merging them. In this paper, we will examine two different kinds of merging cases in the context of partial-order planning. We will see that merging cases can be very difficult if the cases are merged eagerly. On the other hand, if cases are merged by avoiding redundant steps, the guidance of the additional cases tends to decrease with the number of covered goals and retrieved cases in domains having a certain kind of interactions. Thus, to retrieve a single case covering many of the goals of the problem or to retrieve fewer cases covering many of the goals is at least equally effective as to retrieve several cases covering all goals in these domains.
This paper shows an approach to profit from type information about planning objects in a partial-order planner. The approach turns out to combine representational and computational advantages. On the one hand, type hierarchies allow better structuring of domain specifications. On the other hand, operators contain type constraints which reduce the search space of the planner as they partially achieve the functionality of filter conditions.
Viele Entwicklungsprozesse, wie sie z.B. beim Entwurf von grossen Softwaresystemen benötigt werden, basieren in erster Linie auf dem Wissen der mit der Entwicklung betrauten Mitarbeiter. Mit wachsender Komplexität der Entwurfsaufgaben und mit wachsender Anzahl der Mitarbeiter in einem Projekt wird die Koordination und Verteilung dieses Wissens immer problematischer. Aus diesem Grund versucht man zunehmend, das Wissen der Mitarbeiter in elektronischer Form, d.h. in Rechnern zu speichern und zu verwalten. Dadurch, dass der Entwurf eines komplexen Systems ebenfalls am Rechner modelliert wird, steht benötigtes Wissen sofort zur Verfügung und kann zur Entscheidungsunterstützung herangezogen werden. Gerade bei der Planung grosser Projekte stehen jedoch oft Entscheidungen aus, die erst später, während der Abwicklung getroffen werden können. Da gängige Workflow-Management-System zumeist eine komplette Modellierung verlangen, bevor die Abwicklung eines Projektmodells beginnen kann, habt sich dieser Ansatz gerade für umfangreiche Projekte als eher ungeeignet herausgestellt.
Like other industries, the aircraft industry is under high pressure to meet drastically increased customer goals for market price and flexibility. This while at the same time share holders request for short term profit guarantees. Daimler-Benz Aerospace Airbus has met this challenge using business process reengineering methods which led to total company restructuring from functional orientation to customer and product orientation. This paper will show how business process modelling techniques have been applied. Especially concurrent engineering methods are used to integrate the various disciplines involved from market analysts over design, commercial to industrialization staff.
This paper describes an Internet-scalable knowledge base infrastructure for managing the knowledge used by an in-telligent software productivity infrastructure system. The infrastructure provides workable solutions for several significant issues: (1) Internetunique names for pieces of knowledge; (2) multi-platform, multi-language support; (3) distributed knowledge base synchronization mechanisms; (4) support for extensive customized variations in knowledge content, and (5) knowledge caching mechanisms for improved system performance. The infrastructure described here is a workable example of the kind of infrastructure that will be required to manage the evolution and reuse of millions of pieces of knowledge in the future.
This paper describes our experiences in modeling entire software products (trees of software files) as objects. Container pnodes (product nodes) have user-defined Internetunique names, data types, and methods (operations). Pnodes can contain arbitrary collections of software files that represent programs, libraries, documents, or other software products. Pnodes can contain multiple software products, so that header files, libraries, and program products may all be stored within one pnode. Pnodes can contain views that list other pnodes in order to form large conceptual structures of pnodes. Typical pnode -object methods include: fetching and storing into version controlled repositories; dynamic analysis of pnode contents to generate makefiles of arbitrary complexity; local automated build operations; Internet-scalable distributed repository synchroni- zations; Internet-scalable, multi-platform, distributed build operations; extraction and generation of online API documen- tation, spell checking of document pnodes, and so on. Since methods are user-defined, they can be arbitrarily complex. Modelling software products as objects provides a large amount of effort leverage, since one person can define the methods and many people can use them in extensively automated ways.
Techniques for modular software design are presented applying software agents. The conceptual designs are domain independent and make use of specificdomain aspects applying Multiagent AI. The stages of conceptualization, design and implementation are defined by new techniques coordinated by objects. Software systemsare designed by knowledge acquisition, specification, and multiagent implementations.