GWAI-90 14th German Workshop on Artificial Intelligence

GWAI-90 14th German Workshop on Artificial Intelligence

Author: Heinz Marburger

Publisher: Springer

Published: 1990

Total Pages: 348

ISBN-13: 9783540531326

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Auf der "GWAI-90 - 14th German Workshop on Artificial Intelligence" wurden auch in diesem Jahr im Vortragsprogramm und in fünf speziellen Workshops aktuelle KI-Forschungsergebnisse präsentiert sowie in zwei Tutorien Grundlagen von KI-Teilgebieten dargestellt. Der vorliegende Band enthält die Texte der 34 Vorträge und der zwei eingeladenen Hauptvorträge. Die angesprochenen Themenbereiche der KI sind: Wissensrepräsentation, Mensch-Computer-Interaktion, Expertensysteme, Kognition, Deduktion, Natürlichsprachliche Systeme, Maschinelles Lernen, Bildverstehen und KI-Programmiersprachen. Sowohl die Verteilung der Beiträge in diesem Band als auch die der eingereichten Beiträge auf die KI-Gebiete deutet auf eine Konzentration der Forschungsaktivitäten auf Natürlichsprachliche Systeme und Wissensrepräsentation hin.


Begründungsverwaltung

Begründungsverwaltung

Author: Herbert Stoyan

Publisher: Springer Science & Business Media

Published: 2013-03-07

Total Pages: 161

ISBN-13: 3642733859

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Dieses Buch enthält die schriftlichen Ausarbeitungen von Vorträgen, die am 9. Oktober 1986 auf einem Workshop über Reason Maintenance gehalten worden sind. Der Begriff Begründungsverwaltung als Übersetzung von Reason Maintenance soll die Gleichzeitigkeit der Aspekte der Speicherung und Aufbewahrung der Begründungen und der Erhaltung der Gültigkeit von Aussagen auf Grund der gültigen Begründungen ausdrücken. Reason Maintenance ist eine Fortführung und Verallgemeinerung von Truth Maintenance. Truth-Maintenance-Systeme sind Programmsysteme, die Speicher von Aussagen realisieren, die weitgehend nur auf aussagenlogischer Ebene formalisiert sind. Sie verwalten Aussagenmengen und ihre Bewertungen. Annahmen und einfache Konsequenzen aus ihnen werden in einer Weise aufbewahrt, da€ eine widerspruchsfreie Aussagenmenge zu jedem konkreten Zeitpunkt erkennbar ist. Die Technik, mit der dieses Ziel erreicht wird, besteht in der Repräsentation der Beziehungen zwischen den Aussagen und in der Aufbewahrung der Prämissen, Implikationen und Schlu€regeln, die zur Ableitung einer bestimmten Aussage verwendet worden sind. Der Zweck dieser Systeme ist demnach Konsistenzerhaltung durch Begründungsverwaltung. Die vorliegenden Arbeiten repräsentieren den deutschen Wissensstand auf diesem Teilgebiet der Künstlichen Intelligenz unter Betonung des Ansatzes von de Kleer. Damit führt dieser Band den Leser an wesentliche aktuelle Forschungsergebnisse heran.


Fehlertolerierende Rechensysteme / Fault-Tolerant Computing Systems

Fehlertolerierende Rechensysteme / Fault-Tolerant Computing Systems

Author: Fevzi Belli

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 401

ISBN-13: 3642456286

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Dieser Band enthält die 38 Beiträge der 3. GI/ITG/GMA-Fachtagung über "Fehlertolerierende Rechensysteme". Unter den 10 aus dem Ausland eingegangenen Beiträgen sind 4 eingeladene Vorträge. Insgesamt dokumentiert dieser Tagungsband die Entwicklung der Konzeption und Implementierung fehlertoleranter Systeme in den letzten drei Jahren vor allem in Europa. Sämtliche Beiträge sind neue Forschungs- oder Entwicklungsergebnisse, die vom Programmausschuß der Tagung aus 70 eingereichten Beiträgen ausgewählt wurden.


Machine Learning: ECML-93

Machine Learning: ECML-93

Author: Pavel B. Brazdil

Publisher: Springer Science & Business Media

Published: 1993-03-23

Total Pages: 492

ISBN-13: 9783540566021

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This volume contains the proceedings of the Eurpoean Conference on Machine Learning (ECML-93), continuing the tradition of the five earlier EWSLs (European Working Sessions on Learning). The aim of these conferences is to provide a platform for presenting the latest results in the area of machine learning. The ECML-93 programme included invited talks, selected papers, and the presentation of ongoing work in poster sessions. The programme was completed by several workshops on specific topics. The volume contains papers related to all these activities. The first chapter of the proceedings contains two invited papers, one by Ross Quinlan and one by Stephen Muggleton on inductive logic programming. The second chapter contains 18 scientific papers accepted for the main sessions of the conference. The third chapter contains 18 shorter position papers. The final chapter includes three overview papers related to the ECML-93 workshops.


Concept Formation and Knowledge Revision

Concept Formation and Knowledge Revision

Author: Stefan Wrobel

Publisher: Springer Science & Business Media

Published: 2013-03-14

Total Pages: 250

ISBN-13: 1475723172

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A fundamental assumption of work in artificial intelligence and machine learning is that knowledge is expressed in a computer with the help of knowledge representations. Since the proper choice of such representations is a difficult task that fundamentally affects the capabilities of a system, the problem of automatic representation change is an important topic in current research. Concept Formation and Knowledge Revision focuses on representation change as a concept formation task, regarding concepts as the elementary representational vocabulary from which further statements are constructed. Taking an interdisciplinary approach from psychological foundations to computer implementations, the book draws on existing psychological results about the nature of human concepts and concept formation to determine the scope of concept formation phenomena, and to identify potential components of computational concept formation models. The central idea of this work is that computational concept formation can usefully be understood as a process that is triggered in a demand-driven fashion by the representational needs of the learning system, and identify the knowledge revision activities of a system as a particular context for such a process. The book presents a detailed analysis of the revision problem for first-order clausal theories, and develops a set of postulates that any such operation should satisfy. It shows how a minimum theory revision operator can be realized by using exception sets, and that this operator is indeed maximally general. The book then shows that concept formation can be triggered from within the knowledge revision process whenever the existing representation does not permit the plausible reformulation of an exception set, demonstrating the usefulness of the approach both theoretically and empirically within the learning knowledge acquisition system MOBAL. In using a first-order representation, this book is part of the rapidly developing field of Inductive Logic Programming (ILP). By integrating the computational issues with psychological and fundamental discussions of concept formation phenomena, the book will be of interest to readers both theoretically and psychologically inclined. From the foreword by Katharina Morik: ` The ideal to combine the three sources of artificial intelligence research has almost never been reached. Such a combined and integrated research requires the researcher to master different ways of thinking, different work styles, different sets of literature, and different research procedures. It requires capabilities in software engineering for the application part, in theoretical computer science for the theory part, and in psychology for the cognitive part. The most important capability for artificial intelligence is to keep the integrative view and to create a true original work that goes beyond the collection of pieces from different fields. This book achieves such an integrative view of concept formation and knowledge revision by presenting the way from psychological investigations that indicate that concepts are theories and point at the important role of a demand for learning. to an implemented system which supports users in their tasks when working with a knowledge base and its theoretical foundation. '


CSL '87

CSL '87

Author: Egon Börger

Publisher: Springer Science & Business Media

Published: 1988-09-14

Total Pages: 356

ISBN-13: 9783540502418

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This volume contains the papers which were presented to the workshop "Computer-Science Logic" held in Karlsruhe on October 12-16, 1987. Traditionally Logic, or more specifically, Mathematical Logic splits into several subareas: Set Theory, Proof Theory, Recursion Theory, and Model Theory. In addition there is what sometimes is called Philosophical Logic which deals with topics like nonclassical logics and which for historical reasons has been developed mainly at philosphical departments rather than at mathematics institutions. Today Computer Science challenges Logic in a new way. The theoretical analysis of problems in Computer Science for intrinsic reasons has pointed back to Logic. A broad class of questions became visible which is of a basically logical nature. These questions are often related to some of the traditional disciplines of Logic but normally without being covered adequately by any of them. The novel and unifying aspect of this new branch of Logic is the algorithmic point of view which is based on experiences people had with computers. The aim of the "Computer-Science Logic" workshop and of this volume is to represent the richness of research activities in this field in the German-speaking countries and to point to their underlying general logical principles.


9th International Conference on Automated Deduction

9th International Conference on Automated Deduction

Author: Ewing Lusk

Publisher: Springer Science & Business Media

Published: 1988-05-04

Total Pages: 778

ISBN-13: 9783540193432

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This volume contains the papers presented at the Ninth International Conference on Automated Deduction (CADE-9) held May 23-26 at Argonne National Laboratory, Argonne, Illinois. The conference commemorates the twenty-fifth anniversary of the discovery of the resolution principle, which took place during the summer of 1963. The CADE conferences are a forum for reporting on research on all aspects of automated deduction, including theorem proving, logic programming, unification, deductive databases, term rewriting, ATP for non-standard logics, and program verification. All papers submitted to the conference were refereed by at least two referees, and the program committee accepted the 52 that appear here. Also included in this volume are abstracts of 21 implementations of automated deduction systems.


Recent Advances in Robot Learning

Recent Advances in Robot Learning

Author: Judy A. Franklin

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 218

ISBN-13: 1461304717

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Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration and concept formulation. While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems. Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution. Since robot learning involves decision making, there is an inherent active learning issue. Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data. Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints. These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning. On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution. Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3).