One of the most important reasons for the current intensity of interest in agent technology is that the concept of an agent, as an autonomous system capable of interacting with other agents in order to satisfy its design objectives, is a natural one for software designers. Just as we can understand many systems as being composed of essentially passive objects, which have a state and upon which we can perform operations, so we can understand many others as being made up of interacting semi-autonomous agents. This book brings together revised versions of papers presented at the First International Workshop on Agent-Oriented Software Engineering, AOSE 2000, held in Limerick, Ireland, in conjunction with ICSE 2000, and several invited papers. As a comprehensive and competent overview of agent-oriented software engineering, the book addresses software engineers interested in the new paradigm and technology as well as research and development professionals active in agent technology.

Presents a methodology developed by DaimlerChrysler.

Illustrates the methodology through detailed case studies.

Game Theory And Decision Theory In Agent-Based Systems is a collection of papers from international leading researchers, that offers a broad view of the many ways game theory and decision theory can be applied in agent-based systems, from standard applications of the core elements of the theory to more cutting edge developments. The range of topics discussed in this book provide the reader with the first comprehensive volume that reflects both the depth and breadth of work in applying techniques from game theory and decision theory to design agent-based systems. Chapters include:

• Selecting Partners;
• Evolution of Agents with Moral Sentiments in an IPD Exercise;
• Dynamic Desires;
• Emotions and Personality;
• Decision-Theoretic Approach to Game Theory;
• Shopbot Economics;
• Finding the Best Way to Join in;
• Shopbots and Pricebots in Electronic Service Markets;
• Polynomial Time Mechanisms;
• Multi-Agent Q-learning and Regression Trees;
• Satisficing Equilibria;
• Investigating Commitment Flexibility in Multi-agent Contracts;
• Pricing in Agent Economies using Multi-agent Q-learning;
• Using Hypergames to Increase Planned Payoff and Reduce Risk;
• Bilateral Negotiation with Incomplete and Uncertain Information;
• Robust Combinatorial Auction Protocol against False-name Bids.

This volume represents an advanced, comprehensive state-of-the-art survey of the field of rational agency as it stands today. It covers the philosophical foundations of rational agency, logical and decision-theoretic approaches to rational agency, multi-agent aspects of rational agency and a number of approaches to programming rational agents. It will be of interest to researchers in logic, mainstream computer science, the philosophy of rational action and agency, and economics.

With an increasing number of applications in the context of multi-agent systems, automated negotiation is a rapidly growing area. Written by top researchers in the field, this state-of-the-art treatment of the subject explores key issues involved in the design of negotiating agents, covering strategic, heuristic, and axiomatic approaches. The authors discuss the potential benefits of automated negotiation as well as the unique challenges it poses for computer scientists and for researchers in artificial intelligence. They also consider possible applications and give readers a feel for the types of domains where automated negotiation is already being deployed. This book is ideal for graduate students and researchers in computer science who are interested in multi-agent systems. It will also appeal to negotiation researchers from disciplines such as management and business studies, psychology and economics.

Game Theory And Decision Theory In Agent-Based Systems is a collection of papers from international leading researchers, that offers a broad view of the many ways game theory and decision theory can be applied in agent-based systems, from standard applications of the core elements of the theory to more cutting edge developments. The range of topics discussed in this book provide the reader with the first comprehensive volume that reflects both the depth and breadth of work in applying techniques from game theory and decision theory to design agent-based systems.Chapters include: * Selecting Partners; * Evolution of Agents with Moral Sentiments in an IPD Exercise; * Dynamic Desires; * Emotions and Personality; * Decision-Theoretic Approach to Game Theory; * Shopbot Economics; * Finding the Best Way to Join in; * Shopbots and Pricebots in Electronic Service Markets; * Polynomial Time Mechanisms; * Multi-Agent Q-learning and Regression Trees; * Satisficing Equilibria; * Investigating Commitment Flexibility in Multi-agent Contracts; * Pricing in Agent Economies using Multi-agent Q-learning; * Using Hypergames to Increase Planned Payoff and Reduce Risk; * Bilateral Negotiation with Incomplete and Uncertain Information; * Robust Combinatorial Auction Protocol against False-name Bids.

Cooperative game theory is a branch of (micro-)economics that studies the behavior of self-interested agents in strategic settings where binding agreements among agents are possible. Our aim in this book is to present a survey of work on the computational aspects of cooperative game theory. We begin by formally defining transferable utility games in characteristic function form, and introducing key solution concepts such as the core and the Shapley value. We then discuss two major issues that arise when considering such games from a computational perspective: identifying compact representations for games, and the closely related problem of efficiently computing solution concepts for games. We survey several formalisms for cooperative games that have been proposed in the literature, including, for example, cooperative games defined on networks, as well as general compact representation schemes such as MC-nets and skill games. As a detailed case study, we consider weighted voting games: a widely-used and practically important class of cooperative games that inherently have a natural compact representation. We investigate the complexity of solution concepts for such games, and generalizations of them. We briefly discuss games with non-transferable utility and partition function games. We then overview algorithms for identifying welfare-maximizing coalition structures and methods used by rational agents to form coalitions (even under uncertainty), including bargaining algorithms. We conclude by considering some developing topics, applications, and future research directions.

Over the past decade, rational agency has come to be recognised as a central theme in artificial intelligence. Drawing upon research on rational action and agency in philosophy, logic, game theory, decision theory, and the philosophy of language, this volume represents an advanced, comprehensive state-of-the-art survey of the field of rational agency as it stands today. It covers the philosophical foundations of rational agency, logical and decision-theoretic approaches to rational agency, multi-agent aspects of rational agency (including speech acts, joint plans, and cooperation protocols), and, finally, describes a number of approaches to programming rational agents. Although written from the standpoint of artificial intelligence, this interdisciplinary text will be of interest to researchers in logic, mainstream computer science, the philosophy of rational action and agency, and economics.

Presents a methodology developed by DaimlerChrysler.

Illustrates the methodology through detailed case studies.

This book constitutes the thoroughly refereed post-workshop proceedings of the 5th Workshop on Model Checking and Artificial Intelligence, MOCHART 2008, held in Patras, Greece, in July 2008 as a satellite event of ECAI 2008, the 18th biannual European conference on Artificial Intelligence.

The 9 revised full workshop papers presented together with 2 invited lectures have gone through two rounds of reviewing and improvement and were carefully selected for inclusion in the book. The workshop covers all ideas, research, experiments and tools that relate to both MC and AI fields.

This book is based on the second International Workshop on Agent Theories, Architectures, and Languages, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95 in Montreal, Canada in August 1995.
The 26 papers are revised final versions of the workshop presentations selected from a total of 54 submissions; also included is a comprehensive introduction, a detailed bibliography listing 355 relevant publications, and a subject index. The book is structured into seven sections, reflecting the most current major directions in agent-related research. Together with its predecessor, Intelligent Agents, published as volume 890 in the LNAI series, this book provides a timely and comprehensive state-of-the-art report.

'A terrific book - essential reading for everyone seeking to make sense of Artificial Intelligence' Professor Sir Adrian Smith, Director and Chief Executive of the Alan Turing Institute In this myth-busting guide to AI past and present, one of the world's leading researchers shows why our fears for the future are misplaced. The ultimate dream of AI is to build machines that are like us: conscious and self-aware. While this remains a remote possibility, rapid progress in AI is already transforming our world. Yet the public debate is still largely centred on unlikely prospects, from sentient machines to dystopian robot takeovers. In this lively and clear-headed guide, Michael Wooldridge challenges the prevailing narrative, revealing how the hype distracts us from both the more immediate risks that this technology poses - from algorithmic bias to fake news - and the true life-changing potential of the field. The Road to Conscious Machines elucidates the discoveries of AI's greatest pioneers from Alan Turing to Demis Hassabis, and what today's researchers actually think and do. 'Nobody understands the past, the present, the promise and the peril of this new technology better than Michael Wooldridge. The definitive account' Matt Ridley, author of The Rational Optimist 'Effortlessly readable. The perfect guide to the history and future of AI' Tom Chivers, author of The AI Does Not Hate You

'I propose to consider the question, 'Can machines think?' Alan Turing (1950) Part of the ALL-NEW Ladybird Expert series. This book is for everyone living in the age of Artificial Intelligence. And this is an accessible and authoritative introduction to one of the most important conversations of our time . . . Written by computer scientist Michael Wooldridge, Artificial Intelligence chronicles the development of intelligent machines, from Turing's dream of machines that think, to today's digital assistants like Siri and Alexa. AI is not something that awaits us in the future. Inside you'll learn how we have come to rely on embedded AI software and what a world of ubiquitous AI might look like. What's inside? - The British mathematician Alan Turing - Can machines 'understand'? - Logical and Behavioural AI - The reality of AI today - AI tomorrow - And much more . . . For an adult readership, the Ladybird Expert series is produced in the same iconic small hardback format pioneered by the original Ladybirds. Each beautifully illustrated book features the first new illustrations produced in the original Ladybird style for nearly forty years.

Penguin Readers is an ELT graded reader series for learners of English as a foreign language. With carefully adapted text, new illustrations and language learning exercises, the print edition also includes instructions to access supporting material online. Titles include popular classics, exciting contemporary fiction, and thought-provoking non-fiction, introducing language learners to bestselling authors and compelling content. The eight levels of Penguin Readers follow the Common European Framework of Reference for language learning (CEFR). Exercises at the back of each Reader help language learners to practise grammar, vocabulary, and key exam skills. Before, during and after-reading questions test readers' story comprehension and develop vocabulary. Artificial Intelligence, a Level 7 Reader, is B2 in the CEFR framework. The longer text is made up of sentences with up to four clauses, introducing future perfect simple, mixed conditionals, past perfect continuous, mixed conditionals, more complex passive forms and modals for deduction in the past. This book aims to explain what AI is and what it is not. It turns to different subjects to understand AI, and what it means for the world. It also examines important AI developments in the past, present and future. Visit the Penguin Readers website Exclusively with the print edition, readers can unlock online resources including a digital book, audio edition, lesson plans and answer keys.