Most artificial intelligence research investigates intelligent behavior for a single agent--solving problems heuristically, understanding natural language, and so on. Distributed Artificial Intelligence (DAI) is concerned with coordinated intelligent behavior: intelligent agents coordinating their knowledge, skills, and plans to act or solve problems, working toward a single goal, or toward separate, individual goals that interact. DAI provides intellectual insights about organization, interaction, and problem solving among intelligent agents. This comprehensive collection of articles shows the breadth and depth of DAI research. The selected information is relevant to emerging DAI technologies as well as to practical problems in artificial intelligence, distributed computing systems, and human-computer interaction. "Readings in Distributed Artificial Intelligence" proposes a framework for understanding the problems and possibilities of DAI. It divides the study into three realms: the natural systems approach (emulating strategies and representations people use to coordinate their activities), the engineering/science perspective (building automated, coordinated problem solvers for specific applications), and a third, hybrid approach that is useful in analyzing and developing mixed collections of machines and human agents working together. The editors introduce the volume with an important survey of the motivations, research, and results of work in DAI. This historical and conceptual overview combines with chapter introductions to guide the reader through this fascinating field. A unique and extensive bibliography is also provided.

Distributed Artificial Intelligence (DAI) is a dynamic area of research and this book is the first comprehensive, truly integrated exposition of the discipline presenting influential contributions from leaders in the field. Commences with a solid introduction to the theoretical and practical issues of DAI, followed by a discussion of the core research topics--communication, coordination, planning--and how they are related to each other. The third section describes a number of DAI testbeds, illustrating particular strategies commissioned to provide software environments for building and experimenting with DAI systems. The final segment contains contributions which consider DAI from different perspectives.

Distributed AI is the branch of AI concerned with how to coordinate behavior among a collection of semi-autonomous problem-solving agents: how they can coordinate their knowledge, goals and plans to act together, to solve joint problems, or to make individually or globally rational decisions in the face of uncertainty and multiple, conflicting perspectives. Distributed, coordinated systems of problem solvers are rapidly becoming practical partners in critical human problem-solving environments, and DAI is a rapidly developing field of both application and research, experiencing explosive growth around the world. This book presents a collection of articles surveying several major recent developments in DAI. The book focuses on issues that arise in building practical DAI systems in real-world settings, and covers work undertaken in a number of major research and development projects in the U.S. and in Europe. It provides a synthesis of recent thinking, both theoretical and applied, on major problems of DAI in the 1990s.

Distributed Artificial Intelligence

This is the first international conference aimed at bringing the distributed database and distributed AI (DAD experts together, from both academia and industry, in order to discuss the issues of the next generation of knowledge based systems, namely Cooperating Knowledge Based Systems or CKBS for short. As the area of CKBS is new, we intended it to be an ideas conference - a conference where interesting new ideas, rather than results from completed projects, are explored, discussed, and debated. The conference was organised by the DAKE Centre. This is an interdisciplinary centre at the University of Keele for research and development in Data and Knowledge Engineering (DAKE). The Centre draws most of its strength from the Department of Computer Science which also provides administrative support for the activities of the Centre, although its membership is spread over several departments. The Centre has three main streams of research activities, namely: Large Knowledge Bases Software Engineering Neural Networks The Large Knowledge Base group, which provided the focus for this conference, is active in a number of research areas relating to data and knowledge bases, spanning from distributed databases to cooperations among data and knowledge bases. The current research topics include integration of data and knowledge bases and coopera ting knowledge based systems, with several major projects in the latter (see the entries under the Poster Session given below).

Distributed Artificial Intelligence (DAI) came to existence as an approach for solving complex learning, planning, and decision-making problems. When we talk about decision making, there may be some meta-heuristic methods where the problem solving may resemble like operation research. But exactly, it is not related completely to management research. The text examines representing and using organizational knowledge in DAI systems, dynamics of computational ecosystems, and communication-free interactions among rational agents. This publication takes a look at conflict-resolution strategies for nonhierarchical distributed agents, constraint-directed negotiation of resource allocations, and plans for multiple agents. Topics included plan verification, generation, and execution, negotiation operators, representation, network management problem, and conflict-resolution paradigms. The manuscript elaborates on negotiating task decomposition and allocation using partial global planning and mechanisms for assessing nonlocal impact of local decisions in distributed planning. The book will attract researchers and practitioners who are working in management and computer science, and industry persons in need of a beginner to advanced understanding of the basic and advanced concepts.

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.

In these notes on 'Projective Modules and Complete Intersections' an account on the recent developments in research on this subject is presented. The author's preference for the technique of Patching isotopic isomorphisms due to Quillen, formalized by Plumsted, over the techniques of elementary matrices is evident here. The treatment of Basic Element theory here incorporates Plumstead's idea of the 'generalized dimension functions'. These notes are highly selfcontained and should be accessible to any graduate student in commutative algebra or algebraic geometry. They include fully self-contained presentations of the theorems of Ferrand-Szpiro, Cowsik-Nori and the techniques of Lindel.

Intelligent agent and distributed AI (DAI) approaches attach specific conditions to cooperative exchanges between intelligent systems, that go far beyond simple functional interoperability. Ideally, systems that pursue local or global goals, coordinate their actions, share knowledge, and resolve conflicts during their interactions within groups of similar or dissimilar agents can be viewed as cooperative coarse-grained systems. The infrastructure of telecommunications is a world in transition. There are a number of trends that contribute to this: convergence of traditional telephony and data network worlds, blurring of boundaries between public and private networks, complementary evolution of wireline, wireless, and cable network infrastructures, the emergence of integrated broadband multimedia networks and, of course, the information superhighway. Up to now, despite the effort that has gone into this area, the field of intelligent agents research has not yet led to many fielded systems. Telecommunications applications pose strong requirements to agents such as: reliability, real-time performance, openness, security management and other integrated management, and mobility. In order to fulfil their promise, intelligent agents need to be fully dependable and typically require an integrated set of capabilities. This is the challenge that exists for intelligent agents technology in this application domain.

This volume coherently present 24 thoroughly revised full papers accepted for the ECAI-94 Workshop on Agent Theories, Architectures, and Languages. There is currently considerable interest, from both the AI and the mainstream CS communities, in conceptualizing and building complex computer systems as collections of intelligent agents. This book is devoted to theoretical and practical aspects of architectural and language-related design and implementation issues of software agents. Particularly interesting is the comprehensive survey by the volume editors, which outlines the key issues and indicates, via a comprehensive bibliography, topics for further reading. In addition, a glossary of key terms in this emerging field and a comprehensive subject index is included.