Agent-based modelling on a computer appears to have a special role to play in the development of social science. It offers a means of discovering general and applicable social theory, and grounding it in precise assumptions and derivations, whilst addressing those elements of individual cognition that are central to human society. However, there are important questions to be asked and difficulties to overcome in achieving this potential. What differentiates agent-based modelling from traditional computer modelling? Which model types should be used under which circumstances? If it is appropriate to use a complex model, how can it be validated? Is social simulation research to adopt a realist epistemology, or can it operate within a social constructionist framework? What are the sociological concepts of norms and norm processing that could either be used for planned implementation or for identifying equivalents of social norms among co-operative agents? Can sustainability be achieved more easily in a hierarchical agent society than in a society of isolated agents? What examples are there of hybrid forms of interaction between humans and artificial agents? These are some of the sociological questions that are addressed.

These are the proceedings of the Fifth International Workshop on Cooperative Information Agents, held in Modena, Italy, September 6-8, 2001. Information agent technology has become one of the major key technologies for the Internet and the World Wide Web. It mainly emerged as a response to the challenges of cyberspace from both the technological and human user perspective. Development of information agents requires expertise from di?erent research disciplines such as Arti?cial Intelligence (AI), advanced databases and knowledge base systems, distributed information systems, information retrieval, and Human Computer Interaction (HCI). The ?fth international workshop on Cooperative Information Agents (CIA) continued the tradition by capturing the intrinsic interdisciplinary nature of the above research area by calling for contributions from di?erent research communities, and by promoting open and informative discussions on all related topics. In keeping with tradition, the workshop featured a sequence of regular and invited talks of excellence given by leading experts in the ?eld. This year the topics of the talks are mainly on the challenges of information agents in the upcoming age of ubiquitous and pervasive computing. These challenges are in particular due to the necessity of an e?cient utilization, evolution, and trust management of information agents for user-oriented information search, pro- sion, and visualization in networked computing environments with small, mobile, and embedded devices. A di?erent issue concerns the potential of agent-based support of massive distributed data warehousing worldwide.

During the last decades, considerable progress has been observed in all aspects regarding the study of cooperative systems including modeling of cooperative systems, resource allocation, discrete event driven dynamical control, continuous and hybrid dynamical control, and theory of the interaction of information, control, and hierarchy. Solution methods have been proposed using control and optimization approaches, emergent rule based techniques, game theoretic and team theoretic approaches. Measures of performance have been suggested that include the effects of hierarchies and information structures on solutions, performance bounds, concepts of convergence and stability, and problem complexity. These and other topics were discusses at the Second Annual Conference on Cooperative Control and Optimization in Gainesville, Florida. Refereed papers written by selected conference participants from the conference are gathered in this volume, which presents problem models, theoretical results, and algorithms for various aspects of cooperative control. Audience: The book is addressed to faculty, graduate students, and researchers in optimization and control, computer sciences and engineering.

This book contains three well-written research tutorials that inform the graduate reader about the forefront of current research in multi-agent optimization. These tutorials cover topics that have not yet found their way in standard books and offer the reader the unique opportunity to be guided by major researchers in the respective fields. Multi-agent optimization, lying at the intersection of classical optimization, game theory, and variational inequality theory, is at the forefront of modern optimization and has recently undergone a dramatic development. It seems timely to provide an overview that describes in detail ongoing research and important trends. This book concentrates on Distributed Optimization over Networks; Differential Variational Inequalities; and Advanced Decomposition Algorithms for Multi-agent Systems. This book will appeal to both mathematicians and mathematically oriented engineers and will be the source of inspiration for PhD students and researchers.

Cooperative Control of Multi-Agent Systems extends optimal control and adaptive control design methods to multi-agent systems on communication graphs. It develops Riccati design techniques for general linear dynamics for cooperative state feedback design, cooperative observer design, and cooperative dynamic output feedback design. Both continuous-time and discrete-time dynamical multi-agent systems are treated. Optimal cooperative control is introduced and neural adaptive design techniques for multi-agent nonlinear systems with unknown dynamics, which are rarely treated in literature are developed. Results spanning systems with first-, second- and on up to general high-order nonlinear dynamics are presented. Each control methodology proposed is developed by rigorous proofs. All algorithms are justified by simulation examples. The text is self-contained and will serve as an excellent comprehensive source of information for researchers and graduate students working with multi-agent systems.

These arethe proceedingsof the Fourth InternationalWorkshopon Cooperative Information Agents, held in Boston Massachusetts, USA, July 7-9, 2000. Cooperative information agent research and development focused originally onaccessingmultiple,heterogeneous,anddistributedinformationsources. Ga- ingaccesstothesesystems,throughInternetsearchengines,applicationprogram interfaces, wrappers, and web-based screens has been an important focus of - operative intelligent agents. Research has also focused on the integration of this information into a coherent model that combined data and knowledge from the multiple sources. Finally, this information is disseminated to a wide audience, giving rise to issues such as data quality, information pedigree, source reliability, information security, personal privacy, and information value. Research in - operative information agents has expanded to include agent negotiation, agent communities, agent mobility, as well as agent collaboration for information d- covery in constrained environments. TheinterdisciplinaryCIAworkshopseriesencompassesa widevarietyoft- ics dealing with cooperative information agents. All workshop proceedings have been published by Springer as Lecture Notes in Arti?cial Intelligence, Volumes 1202 (1997), 1435 (1998), and 1652 (1999), respectively. This year, the theme of the CIA workshop was ”’The Future of Information Agents in Cyberspace”, a very ?tting topic as the use of agents for information gathering, negotiation, correlation, fusion, and dissemination becomes ever more prevalent. We noted a marked trend in CIA 2000 towards addressing issues related to communities of agents that: (1) negotiate for information resources, (2) build robust ontologies to enhance search capabilities, (3) communicate for planning and problem so- ing, (4) learn and evolve based on their experiences, and (5) assume increasing degrees of autonomy in the control of complex systems.

This book collects the most significant literature on agents in an attempt top forge a broad foundation for the field. Includes papers from the perspectives of AI, databases, distributed computing, and programming languages. The book will be of interest to programmers and developers, especially in Internet areas.

Distributed controller design is generally a challenging task, especially for multi-agent systems with complex dynamics, due to the interconnected effect of the agent dynamics, the interaction graph among agents, and the cooperative control laws. Cooperative Control of Multi-Agent Systems: A Consensus Region Approach offers a systematic framework for designing distributed controllers for multi-agent systems with general linear agent dynamics, linear agent dynamics with uncertainties, and Lipschitz nonlinear agent dynamics. Beginning with an introduction to cooperative control and graph theory, this monograph: Explores the consensus control problem for continuous-time and discrete-time linear multi-agent systems Studies the H∞ and H2 consensus problems for linear multi-agent systems subject to external disturbances Designs distributed adaptive consensus protocols for continuous-time linear multi-agent systems Considers the distributed tracking control problem for linear multi-agent systems with a leader of nonzero control input Examines the distributed containment control problem for the case with multiple leaders Covers the robust cooperative control problem for multi-agent systems with linear nominal agent dynamics subject to heterogeneous matching uncertainties Discusses the global consensus problem for Lipschitz nonlinear multi-agent systems Cooperative Control of Multi-Agent Systems: A Consensus Region Approach provides a novel approach to designing distributed cooperative protocols for multi-agent systems with complex dynamics. The proposed consensus region decouples the design of the feedback gain matrices of the cooperative protocols from the communication graph and serves as a measure for the robustness of the protocols to variations of the communication graph. By exploiting the decoupling feature, adaptive cooperative protocols are presented that can be designed and implemented in a fully distributed fashion.

This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Learning and Adaption in Multi-Agent Systems, LAMAS 2005, held in The Netherlands, in July 2005, as an associated event of AAMAS 2005. The 13 revised papers presented together with two invited talks were carefully reviewed and selected from the lectures given at the workshop.

The characteristics of software systems are undergoing dramatic changes. We are moving rapidly into the age of ubiquitous information services. Persistent computing systems are being embedded in everyday objects. They interact in an autonomouswaywith eachother to provideus with increasinglycomplexservices and functionalities that we can access at any time from anywhere. As a con- quence, not only do the numbers of components of software systems increase; there is also a strong qualitative impact. Software systems are increasingly made up of autonomous, proactive, networked components. These interact with each other in patterns and via mechanisms that can hardly be modeled in terms of classical models of interaction or service-oriented coordination. To some extent, future software systems will exhibit characteristics making them more res- blant of natural systems and societies than of mechanical systems and software architectures. This situation poses exciting challenges to computer scientists and software engineers. Already, software agents and multi-agent systems are recognized as both useful abstractions and e?ective technologies for the modeling and building of complex distributed applications. However, little is done with regard to e?- tive and methodic development of complex software systems in terms of mul- agent societies. An urgent need exists for novel approaches to software modeling and software engineering that enable the successful deployment of software s- tems made up ofa massive number ofautonomous components, and that allowus to control and predict their behaviour.