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.

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.

A clear trend in the study and design of autonomous agents during the late 1990s and early 2000s, has been a growing concern with being able to adjust the autonomy, particularly in the context of interactions between artificial intelligences and humans during space missions. The 11 papers present the state of the field, illustrate maturing trends ranging from analytical and formal approaches to concrete attempts and application problems, and challenge researchers to return to that old- time artificial intelligence. Representing and analyzing adaptive decision-making frameworks, obligations and cooperation as two sides of social responsibility, and policy-based agent directability are among the topics. Annotation (c)2003 Book News, Inc., Portland, OR (booknews.com).

The main concepts and techniques of multi-agent oriented programming, which supports the multi-agent systems paradigm at the programming level. A multi-agent system is an organized ensemble of autonomous, intelligent, goal-oriented entities called agents, communicating with each other and interacting within an environment. This book introduces the main concepts and techniques of multi-agent oriented programming, (MAOP) which supports the multi-agent systems paradigm at the programming level. MAOP provides a structured approach based on three integrated dimensions, which the book examines in detail: the agent dimension, used to design the individual (interacting) entities; the environment dimension, which allows the development of shared resources and connections to the real world; and the organization dimension, which structures the interactions among the autonomous agents and the shared environment.

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

Autonomy arrangements have gradually become more numerous, & different developments in respect of autonomy can be discerned in the fields of international & domestic law. The patterns of autonomy are quite disparate, but because various fields of law treat autonomy in different ways, it is fruitful to inquire into the applications of autonomy & to ask what autonomy as such implies. Autonomy is a multi-faceted phenomenon which on the one hand contains the issue of devolution or decentralization of law-making or other normative powers in the institutional fabric of the country without any minority protection component; on the other hand it may in addition contain an explicit minority protection component designed to offer special protection to minority groups in society. Especially in the latter sense, the issue of effective participation of a minority in the government is an important issue, & in this respect, there is a connection between autonomy & a general understanding of democracy.

Autonomy is a fundamental though contested concept. This book is the first exploration into the nature and scope of personal autonomy in mental disorder, resulting in an important new contribution to the philosophy and psychiatry literature

“An extraordinarily good synthesis from an amazing range of philosophical, legal, and technological sources . . . the book will appeal to legal academics and students, lawyers involved in e-commerce and cyberspace legal issues, technologists, moral philosophers, and intelligent lay readers interested in high tech issues, privacy, [and] robotics.” —Kevin Ashley, University of Pittsburgh School of Law As corporations and government agencies replace human employees with online customer service and automated phone systems, we become accustomed to doing business with nonhuman agents. If artificial intelligence (AI) technology advances as today’s leading researchers predict, these agents may soon function with such limited human input that they appear to act independently. When they achieve that level of autonomy, what legal status should they have? Samir Chopra and Laurence F. White present a carefully reasoned discussion of how existing philosophy and legal theory can accommodate increasingly sophisticated AI technology. Arguing for the legal personhood of an artificial agent, the authors discuss what it means to say it has “knowledge” and the ability to make a decision. They consider key questions such as who must take responsibility for an agent’s actions, whom the agent serves, and whether it could face a conflict of interest.

All aboard The Coding Train! This beginner-friendly creative coding tutorial is designed to grow your skills in a fun, hands-on way as you build simulations of real-world phenomena with “The Coding Train” YouTube star Daniel Shiffman. What if you could re-create the awe-inspiring flocking patterns of birds or the hypnotic dance of fireflies—with code? For over a decade, The Nature of Code has empowered countless readers to do just that, bridging the gap between creative expression and programming. This innovative guide by Daniel Shiffman, creator of the beloved Coding Train, welcomes budding and seasoned programmers alike into a world where code meets playful creativity. This JavaScript-based edition of Shiffman’s groundbreaking work gently unfolds the mysteries of the natural world, turning complex topics like genetic algorithms, physics-based simulations, and neural networks into accessible and visually stunning creations. Embark on this extraordinary adventure with projects involving: A physics engine: Simulate the push and pull of gravitational attraction. Flocking birds: Choreograph the mesmerizing dance of a flock. Branching trees: Grow lifelike and organic tree structures. Neural networks: Craft intelligent systems that learn and adapt. Cellular automata: Uncover the magic of self-organizing patterns. Evolutionary algorithms: Play witness to natural selection in your code. Shiffman’s work has transformed thousands of curious minds into creators, breaking down barriers between science, art, and technology, and inviting readers to see code not just as a tool for tasks but as a canvas for boundless creativity. Whether you’re deciphering the elegant patterns of natural phenomena or crafting your own digital ecosystems, Shiffman’s guidance is sure to inform and inspire. The Nature of Code is not just about coding; it’s about looking at the natural world in a new way and letting its wonders inspire your next creation. Dive in and discover the joy of turning code into art—all while mastering coding fundamentals along the way. NOTE: All examples are written with p5.js, a JavaScript library for creative coding, and are available on the book's website.