This book originates from the First International Workshop on Computational Autonomy -Potential, Risks, Solutions, AUTONOMY 2003, held in Melbourne, Australia in July 2003 as part of AAMAS 2003. In addition to 7 revised selected workshop papers, the volume editors solicited 14 invited papers by leading researchers in the area. The workshop papers and the invited papers present a comprehensive and coherent survey of the state of the art of research on autonomy, capturing various theories of autonomy, perspectives on autonomy in different kinds of agent-based systems, and practical approaches to dealing with agent autonomy.

This book originates from the First International Workshop on Computational Autonomy -Potential, Risks, Solutions, AUTONOMY 2003, held in Melbourne, Australia in July 2003 as part of AAMAS 2003. In addition to 7 revised selected workshop papers, the volume editors solicited 14 invited papers by leading researchers in the area. The workshop papers and the invited papers present a comprehensive and coherent survey of the state of the art of research on autonomy, capturing various theories of autonomy, perspectives on autonomy in different kinds of agent-based systems, and practical approaches to dealing with agent autonomy.

Autonomy is a characterizing notion of agents, and intuitively it is rather unambiguous. The quality of autonomy is recognized when it is perceived or experienced, yet it is difficult to limit autonomy in a definition. The desire to build agents that exhibit a satisfactory quality of autonomy includes agents that have a long life, are highly independent, can harmonize their goals and actions with humans and other agents, and are generally socially adept. Agent Autonomy is a collection of papers from leading international researchers that approximate human intuition, dispel false attributions, and point the way to scholarly thinking about autonomy. A wide array of issues about sharing control and initiative between humans and machines, as well as issues about peer level agent interaction, are addressed.

An autonomous agent is a computational system that acquires sensory data from its environment and decides by itself how to relate the external stimulus to its behaviors in order to attain certain goals. Responding to different stimuli received from its task environment, the agent may select and exhibit different behavioral patterns. The behavioral patterns may be carefully predefined or dynamically acquired by the agent based on some learning and adaptation mechanism(s). In order to achieve structural flexibility, reliability through redundancy, adaptability, and reconfigurability in real-world tasks, some researchers have started to address the issue of multiagent cooperation. Broadly speaking, the power of autonomous agents lies in their ability to deal with unpredictable, dynamically changing environments. Agent-based systems are becoming one of the most important computer technologies, holding out many promises for solving real-world problems. The aims of this book are to provide a guided tour to the pioneering work and the major technical issues in agent research, and to give an in-depth discussion on the computational mechanisms for behavioral engineering in autonomous agents. Through a systematic examination, the book attempts to provide the general design principles for building autonomous agents and the analytical tools for modeling the emerged behavioral properties of a multiagent system. Contents: Behavioral Modeling, Planning, and Learning; Synthetic Autonomy; Dynamics of Distributed Computation; Self-Organized Autonomy in Multi-Agent Systems; Autonomy-Oriented Computation; Dynamics and Complexity of Autonomy-Oriented Computation. Readership: Undergraduate and graduate students in computer science and most engineering disciplines, as well as computer scientists, engineers, researchers and practitioners in the field of machine intelligence.

Designing Autonomous Agents provides a summary and overview of the radically different architectures that have been developed over the past few years for organizing robots. These architectures have led to major breakthroughs that promise to revolutionize the study of autonomous agents and perhaps artificial intelligence in general. The new architectures emphasize more direct coupling of sensing to action, distributedness and decentralization, dynamic interaction with the environment, and intrinsic mechanisms to cope with limited resources and incomplete knowledge. The research discussed here encompasses such important ideas as emergent functionality, task-level decomposition, and reasoning methods such as analogical representations and visual operations that make the task of perception more realistic. Contents A Biological Perspective on Autonomous Agent Design, Randall D. Beer, Hillel J. Chiel, Leon S. Sterling * Elephants Don't Play Chess, Rodney A. Brooks * What Are Plans For? Philip E. Agre and David Chapman * Action and Planning in Embedded Agents, Leslie Pack Kaelbling and Stanley J. Rosenschein * Situated Agents Can Have Goals, Pattie Maes * Exploiting Analogical Representations, Luc Steels * Internalized Plans: A Representation for Action Resources, David W. Payton * Integrating Behavioral, Perceptual, and World Knowledge in Reactive Navigation, Ronald C. Arkin * Symbol Grounding via a Hybrid Architecture in an Autonomous Assembly System, Chris Malcolm and Tim Smithers * Animal Behavior as a Paradigm for Developing Robot Autonomy, Tracy L. Anderson and Max Donath

The concept of an intelligent agent - a computational system capable of performing certain tasks autonomously - derived from the growing potential of digital computers in the mid 20th century and had been widely adopted by the early 1990s. Partly in parallel with this concept, the perspective of ambient intelligence (AmI) emerged in the late 1990s. Agent technology and AmI have many similarities, and the main purpose of this book is to provide an overview of the state-of-the-art of the scientific area that integrates these two. The book addresses a wide variety of topics related to agents and AmI, including theoretical, practical, design, implementation, ethical and philosophical issues. The 12 chapters are arranged in four sections. The first consists of three chapters discussing ethical and philosophical issues; the second part explores various approaches that can be used to develop agent-based AmI Systems; the third part contains three chapters that share the goal to endow AmI systems with useful properties like intelligence and adaptivity and the last section presents concrete applications of agent-based AmI systems. This book provides an insight into recent achievements and future challenges at the intersection of agent technology and ambient intelligence and will assist the development of more intelligent, flexible, effective and user-friendly systems as well as posing critical questions about the future of the role of agents within the AmI perspective.

This collection of recently published and refereed papers comes from workshops and colloquia held over the last two years. The papers describe the development of command and control systems, military communications systems, information systems, surveillance systems, autonomous vehicles, simulators, and HCI. The collection provides for the first time an overview of the most significant advances in the technology of intelligent agents.

This book represents the thoroughly refereed post-proceedings of the 6th International Workshop on Agent-Oriented Software Engineering, AOSE 2005. The 18 revised full papers were carefully selected from 35 submissions during two rounds of reviewing and improvement. The papers are organized in topical sections on modeling tools, analysis and validation tools, multiagent systems design, implementation tools, and experiences and comparative evaluations.