This volume contains the postproceedings of the 1st International Workshop on Computational Autonomy – Potential, Risks, Solutions (AUTONOMY 2003), held at the 2nd International Joint Conference on Autonomous Agents and Multi-agentSystems(AAMAS2003),July14,2003,Melbourne,Australia.Apart from revised versions of the accepted workshop papers, we have included invited contributions from leading experts in the ?eld. With this, the present volume represents the ?rst comprehensive survey of the state-of-the-art of research on autonomy, capturing di?erent theories of autonomy, perspectives on autonomy in di?erent kinds of agent-based systems, and practical approaches to dealing with agent autonomy. Agent orientation refers to a software development perspective that has evolved in the past 25 years in the ?elds of computational agents and multiagent systems. The basic notion underlying this perspective is that of a computational agent, that is, an entity whose behavior deserves to be called ?exible, social, and autonomous. As an autonomous entity, an agent possesses action choice and is at least to some extent capable of deciding and acting under self-control. Through its emphasis on autonomy, agent orientation signi?cantly di?ers from traditional engineering perspectives such as structure orientation or object o- entation. These perspectives are targeted on the development of systems whose behavior is fully determined and controlled by external units (e.g., by a p- grammer at design time and/or a user at run time), and thus inherently fail to capture the notion of 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.

The new edition of an introduction to multiagent systems that captures the state of the art in both theory and practice, suitable as textbook or reference. Multiagent systems are made up of multiple interacting intelligent agents—computational entities to some degree autonomous and able to cooperate, compete, communicate, act flexibly, and exercise control over their behavior within the frame of their objectives. They are the enabling technology for a wide range of advanced applications relying on distributed and parallel processing of data, information, and knowledge relevant in domains ranging from industrial manufacturing to e-commerce to health care. This book offers a state-of-the-art introduction to multiagent systems, covering the field in both breadth and depth, and treating both theory and practice. It is suitable for classroom use or independent study. This second edition has been completely revised, capturing the tremendous developments in multiagent systems since the first edition appeared in 1999. Sixteen of the book's seventeen chapters were written for this edition; all chapters are by leaders in the field, with each author contributing to the broad base of knowledge and experience on which the book rests. The book covers basic concepts of computational agency from the perspective of both individual agents and agent organizations; communication among agents; coordination among agents; distributed cognition; development and engineering of multiagent systems; and background knowledge in logics and game theory. Each chapter includes references, many illustrations and examples, and exercises of varying degrees of difficulty. The chapters and the overall book are designed to be self-contained and understandable without additional material. Supplemental resources are available on the book's Web site. Contributors Rafael Bordini, Felix Brandt, Amit Chopra, Vincent Conitzer, Virginia Dignum, Jürgen Dix, Ed Durfee, Edith Elkind, Ulle Endriss, Alessandro Farinelli, Shaheen Fatima, Michael Fisher, Nicholas R. Jennings, Kevin Leyton-Brown, Evangelos Markakis, Lin Padgham, Julian Padget, Iyad Rahwan, Talal Rahwan, Alex Rogers, Jordi Sabater-Mir, Yoav Shoham, Munindar P. Singh, Kagan Tumer, Karl Tuyls, Wiebe van der Hoek, Laurent Vercouter, Meritxell Vinyals, Michael Winikoff, Michael Wooldridge, Shlomo Zilberstein

Autonomous systems are one of the most important trends for the next generation of control systems. This book is the first to transfer autonomous systems concepts and intelligent agents theory into the control and operation environment of power systems. The focus of this book is to design a future control system architecture for electrical power systems, which copes with the changed requirements concerning complexity and flexibility and includes several applications for power systems. This book draws the whole circle from the theoretical and IT-concept of autonomous systems for power system control over the required knowledge-based methods and their capabilities to concrete applications within this field.

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