Table Of ContentHANDBOOK OF DEFEASIBLE REASONING AND
UNCERTAINTY MANAGEMENT SYSTEMS
VOLUME?
HANDBOOK OF DEFEASIBLE
REASONING AND UNCERTAINTY
MANAGEMENT SYSTEMS
EDITORS:
DOV M. GABBAY
King's College, London, U.K.
PHILIPPE SMETS
IRIDIA -Universite Libre de Bruxelles, Belgium
Volume 1: Quantified Representation of Uncertainty and Imprecision
Edited by P. Smets
Volume 2: Reasoning with Actual and Potential Contradictions
Edited by P. Besnard and A. Hunter
Volume 3: Belief Change
Edited by D. Dubois and H. Prade
Volume 4: Abductive Reasoning and Learning
Edited by Dov M. Gabbay and Rudolf Kruse
Volume 5: Algorithms for Uncertainty and Defeasible Reasoning
Edited by Jiirg Kohlas and Serafin Moral
Volume 6: Dynamics and Management of Reasoning Processes
Edited by J.-J. Ch. Meyer andJ. Treur
Volume 7: Agent-based Defeasible Control in Dynamic Environments
Edited by J.-J. Ch. Meyer and J. Treur
HANDBOOK OF DEFEASIBLE
REASONING AND UNCERTAINTY
MANAGEMENT SYSTEMS
VOLUME?
AGENT-BASED
DEFEASIBLE CONTROL IN
DYNAMIC ENVIRONMENTS
Volume Editors:
J.-J. CH. MEYER
Utrecht University, The Netherlands
and
J. TREUR
Free University, Amsterdam, The Netherlands
SPRINGER-SCIENCE+BUSINESS MEDIA, B.V.
A C.I.P. Catalogue record for this book is available from the Library of Congress.
ISBN 978-90-481-6109-6 ISBN 978-94-017-1741-0 (eBook)
DOI 10.1007/978-94-017-1741-0
Printed on acid-free paper
All Rights Reserved
© 2002 Springer Science+Business Media Dordrecht
Originally published by Kluwer Academic Publishers in 2002
No part of this work may be reproduced, stored in a retrieval system, or transmitted
in any form or by any means, electronic, mechanical, photocopying, microfilming,
recording or otherwise, without written permission from the Publisher, with the exception
of any material supplied specifically for the purpose of being entered
and executed on a computer system, for exclusive use by the purchaser of the work.
CONTENTS
Preface vii
Part 1: Introduction and Basic Concepts
Introduction 3
J.-J. Ch. Meyer and J. Treur
Basic Concepts 9
J.-J.Ch. Meyer and J. Treur
Part II: Modelling Frameworks and Generic Agent Models
Compositional Design of Multi-Agent Systems: Modelling 19
Dynamics and Control
F. M. T. Brazier, C. M. Jonker and J. Treur
Control Techniques for Complex Reasoning: The Case of 65
Milord II
L. Godo, J. Puyol-Gruart and C. Sierra
Coordinating Heterogeneous Components Using Executable 99
Temporal Logic
A. Kellett and M. Fisher
Compositional Design and Reuse of a Generic Agent Model 113
F. M. T. Brazier, C. M. Jonker and J. Treur
Part IliA: Formal Analyis: General Approaches
Semantic Formalisation of Emerging Dynamics of 167
Compositional Agent Systems
F. M. T. Brazier, P. van Eck and J. Treur
v
vi
A Descriptive Dynamic Logic and its Application to Reflective 197
Architectures
C. Sierra, L. Godo, R. LOpez de Mantaras and M. Manzano
Compositional Verification of Multi-Agent Systems in 221
Temporal Multi-Epistemic Logic
J. Engelfriet, C.M. Jonker and J. Treur
Part Ilffi: Formal Analysis: Logics for Agents
Formalising Abilities and Opportunities of Agents 253
B. van Linder, W. van der Hoek and J.-J.Ch. Meyer
Seeing is Believing (And so are Hearing and Jumping) 309
B. van Linder, W. van der Hoek and J.-J.Ch. Meyer
Motivational Attitudes in the KARO Framework 341
J.-J.Ch. Meyer, W. van der Hoek and B. van Linder
Modelling Social Agents: Towards Deliberate Communication 357
F. Dignum and B. van Linder
Part IIIC: Formal Analysis: Reasoning about Dynamics
Reasoning about Action and Change Using Dijkstra's 383
Semantics for Programming Languages
W. Lukaszewicz and E. Madalmska-Bugaj
Reasoning about Action and Change: Actions with Abnormal 399
Effects
W. Lukaszewicz and E. Madalmska-Bugaj
Preferential Action Semantics 411
J.-J.Ch. Meyer and P. Doherty
Reuse and Abstraction in Verification: Agents Acting in 427
Dynamic Environments
C.M. Jonker, J. Treur and W. de Vries
Compositional Verification of a Multi-Agent System for 455
One-to-Many Negotiation
vii
F.M. T. Brazier, F. Cornelissen, R. Gustavsson, C.M. Jonker,
0. Lindeberg. B. Polak and J. Treur
Index 476
PREFACE
This volume, the 7th volume in the DRUMS Handbook series, is part of the
aftermath of the successful ESPRIT project DRUMS (Defeasible Reasoning and
Uncertainty Management Systems) which took place in two stages from 1989-
1996. In the second stage (1993- 1996) a work package was introduced devoted
to the topics Reasoning and Dynamics, covering both the topics of "Dynamics
of Reasoning", where reasoning is viewed as a process, and "Reasoning about
Dynamics", which must be understood as pertaining to how both designers of and
agents within dynamic systems may reason about these systems.
The present volume presents work done in this context extended with some
work done by outstanding researchers outside the project on related issues. While
the previous volume in this series had its focus on the dynamics of reasoning pro
cesses, the present volume is more focused on "reasoning about dynamics', viz.
how (human and artificial) agents reason about (systems in) dynamic environments
in order to control them. In particular we consider modelling frameworks and
generic agent models for modelling these dynamic systems and formal approaches
to these systems such as logics for agents and formal means to reason about agent
based and compositional systems, and action & change more in general.
We take this opportunity to mention that we have very pleasant recollections of
the project, with its lively workshops and other meetings, with the many sites and
researchers involved, both within and outside our own work package.
We thank everyone involved, in particular the authors of the papers of this vol
ume, and the series editors Dov Gabbay and Philippe Smets for their encourage
ment and patience. Philippe has also been the overall project leader with a good
taste for the quality of both science and life (including food). The meetings he
organised were always accompanied by excellent wining and dining, thus helping
the project members to get into the right DRUMS spirit. Last, but by no means
least, we thank Jane Spurr for the splendid job she did (again), helping us to get
this volume together, and in particular for the meticulous translation of Word files
into Latex, ably helped by Anna Maros.
John-Jules Meyer
Jan Treur
IX
PART I
INTRODUCTION AND BASIC CONCEPTS
JOHN-JULES MEYER AND JAN TREUR
INTRODUCTION
PART I- GENERAL
One of the recognized problems in AI is the gap between applications and
formal foundations. This book (as the previous one in the DRUMS Hand
book series) does not present the final solution to this problem, but at least
does an attempt to reduce the gap by bringing together state-of-the-art ma
terial from both sides and to clarify their mutual relation. In this book the
main theme is agents and dynamics: dynamics of reasoning processes (as
we have seen in the previous volume in this series), but also dynamics of
the external world. Agents often reason about both types of dynamics.
Agents are {hardware or software) entities that act on the basis of a
"mental state". They possess both informational and motivational atti
tudes, which means that while performing their actions they are guided by
their knowledge and beliefs as well as their desires, intentions and goals
(often referred to as 'BDI notions'), and, moreover, they are able to modify
their knowledge, intentions, etc. in the process of acting as well. Clearly
the description of agent behaviour involves reasoning about the dynamics
of acting, and if agents are supposed to be reflective, they should also them
selves be able to do so. Furthermore, since the actions of agents may -
apart from actions that change the external world directly - also include
reasoning (for example, performing some belief-revising action or an action
comprising of reasoning by default), it may be clear that in the context of
agent systems the dynamics of reasoning (as a special kind of mental action)
and reasoning about dynamics go hand in hand.
PART II- MODELLING
The different phenomena to be modelled in real-world applications show a
very wide variety. To model them, models covering quite different aspects
are needed. One approach is to build a large collection of models for each
phenomenon separately. Another approach is to define one "grand universal
model" that covers as many of the phenomena as possible. Both solutions
have serious drawbacks. The first solution would end up in a large and ad
hoc collection of non-related models. The second solution would impose very
high requirements on the universal model to be developed; any proposed
model would have strong limitations. Besides, a very complex model would
result from which in a given application only a small part is relevant.
The solution that has been chosen in practice, in a sense combines the
two options pointed out. Indeed generic models for different phenomena
3
J.J.Ch. Meyer and J. Treur (eds.).
Handbook of Defeasible Reasoning and Uncertainty Management Systems, Vol. 7, 3-8.
© 2002 Kluwer Academic Publishers.
