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HANDBOOK 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.