Readings In Distributed Artificial Intelligence

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.

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 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

Distributed Artificial Intelligence presents a collection of papers describing the state of research in distributed artificial intelligence (DAI). DAI is concerned with the cooperative solution of problems by a decentralized group of agents. The agents may range from simple processing elements to complex entities exhibiting rational behavior. The book is organized into three parts. Part I addresses ways to develop control abstractions that efficiently guide problem-solving; communication abstractions that yield cooperation; and description abstractions that result in effective organizational structure. Part II describes architectures for developing and testing DAI systems. Part III discusses applications of DAI in manufacturing, office automation, and man-machine interactions. This book is intended for researchers, system developers, and students in artificial intelligence and related disciplines. It can also be used as a reference for students and researchers in other disciplines, such as psychology, philosophy, robotics, and distributed computing, who wish to understand the issues of DAI.

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.