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From An Introduction to Multiagent Systems
Multiagent systems are systems composed of multiple interacting computing ele- ments, known as agents. Agents are computer systems with two important capa- bilities. First, they are at least to some extent capable of autonomous action – of deciding for themselves what they need to do in order to satisfy their design objec- Lives. Second, they are capable of interacting with other agenls – not simply by exchanging data, but by engaging in analogues of the kind of social activity that we all engage in every day of our lives: cooperation, coordination, negotiation, and the like.
—Multiagent systems are a relatively new sub-field of computer science – they have only been studied since about 1980, and the field has only gained widespread recognition since about the mid-1 QQOs. However, since then international interest in the field has grown enormously. This rapid growth has been spurred at least in part by the belief that agents are an appropriate software paradigm through which to exploit the possibilities presented by massive open distributed systems – such as the Internet. Although they will certainly have a pivotal role to play in exploiting the potential of the Internet, there is a lot more to multiagent systems than this. Multiagent systems seem to be a natural metaphor for understanding and building a wide range of what we might crudely call artificial social systems. The ideas of multiagent systems are not tied to a single application domain, but, like objects before them, seem to find currency in a host of different application domains.
My intention in writing this book is simple. I aim to introduce the main issues in the theory and practice of multiagent systems in a way that will be accessible to anyone with a basic background in computer science/IT. The book is deliberately intended to sit on the fence between science and engineering. Thus, as well as discussing the principles and issues in the theory of multiagent systems (i.e. the science of multiagent systems), I very much hope that I manage to communicate something of how to build such systems (i.e. multiagent systems engineering).
The multiagent systems field can be understood as consisting of two closely interwoven strands of work. The first is concerned with individual agents, while the second is concerned with collections of these agents. The structure of the book reflects this division. The first part of the book – Chapter 1 – sets the scene by discussing where the multiagent system field emerged from, and presenting some visions of where it is going. The second part – Chapters 2-5 inclusive—arc con- cerned with individual agents. Following an introduction to the concept of agents, their environments, and the various ways in which we might tell agents what to do, I describe and contrast the main techniques that have been proposed in the literature for building agents. Thus I discuss agents that decide what to do via logical deduction, agents in which decision making resembles the process of prac- tical reasoning in humans, agents that do not explicitly reason at all, and, finally, agents that make decisions by combining deductive and other decision-making mechanisms. In the third part of the book – Chapters 6-10 inclusive – 1 focus on collections of agents. Following a discussion on the various ways in which multi- agent encounters and interactions can be classified, I discuss the ways in which self-interested agents can reach agreements, communicate with one another, and work together. 1 also discuss some of the main approaches proposed for designing multiagent systems. The fourth and final part of the book presents two advanced supplemental chapters, on applications of agent systems, and formal methods for reasoning about agent systems, respectively.
I have assumed that the main audience for the book will be undergraduate students of computer science/IT – the book should be suitable for such students in their second or third year of study. However, I also hope that the book will be accessible to coniputing/TT professionals, who wish to know more about some of the ideas driving one of the major areas of research and development activity in computing today
1 Introduction
1.1 The Vision Thing
1.2 Some Views of the Field
1.3 Objections to Multiagent Systems
2 Intelligent Agents
2.1 Environments
2.2 Intelligent Agents
2.3 Agents and Objects
2.4 Agents and Expert Systems
2.5 Agents as Intentional Systems
2.6 Abstract Architectures for Intelligent Agents
2.7 How to Tell an Agent What to Do
2.8 Synthesizing Agents
3 Deductive Reasoning Agents
3.1 Agents as Theorem Provers
3.2 Agent-Oriented Programming
3.3 Concurrent MetateM
4 Practical Reasoning Agents
4.1 Practical Reasoning Equals Deliberation Plus Means-Ends Reasoning
4.2 Means-Ends Reasoning
4.3 Implementing a Practical Reasoning Agent
4.4 HOMER: an Agent That Plans
4.5 The Procedural Reasoning Systpm
5 Reactive and Hybrid Agents
5.1 Brooks and the Subsumption Architecture
5.2 The Limitations of Reactive Agents
5.3 Hybrid Agents
5.3.1 TouringMachines
5.3.2 InteRRaP
6 Multiagent Interactions
6.1 Utilities and Preferences
6.2 Multiagent Encounters
6.3 Dominant Strategies and Nash Equilibria
6.4 Competitive and Zero-Sum Interactions
6.5 The Prisoner’s Dilemma
6.6 Other Symmetric 2 x 2 Interactions
6.7 Dependence Relations in Multiagent Systems
7 Reaching Agreements
7.1 Mechanism Design
7.2 Auctions
7.3 Negotiation
7.3.1 Task-oriented domains
7.3.2 Worth-oriented domains
7.4 Argumentation
8 Communication
8.1 Speech Acts
8.2 Agent CommunicationLanguages
8.3 Ontologies for Agent Communication
8.4 Coordination Languages
9 Working Together
9.1 Cooperative Distributed Problem Solving
9.2 Task Sharing and Result Sharing
9.3 Result Sharing
9.4 Combining Task and Result Sharing
9.5 Handling Inconsistency
9.6 Coordination
9.6.1 Coordination through partial global planning
9.6.2 Coordination through joint intentions
9.6.3 Coordination by mutual modelling
9.6.4 Coordination by norms and social laws
10 Methodologies
10.1 When is an Agent-Based Solution Appropriate?
10.2 Agent-Oriented Analysis and Design Techniques
10.3 Pitfalls of Agent Development
10.4 Mobile Agents
11 Applications
11.1 Agents for Workflow and Business Process Management
11.2 Agents for Distributed Sensing
11.3 Agents for Information Retrieval and Management
Multiagent information retrieval systems
FAQ-finders
Expertise finders
Indexing agents
Tour guides
Etzioni and Weld (1995) identify the following specific types of Web-based agent they believe are likely to emerge in the near future
Personal information agents
11.4 Agents for Electronic Commerce
11.5 Agents for Human-Computer Interfaces
11.6 Agents for Virtual Environments
11.7 Agents for Social Simulation
11.8 Agents for X
12 Logics for Multiagent Systems
12.1 Why Modal Logic?
12.2 Possible-Worlds Semantics for Modal Logics
12.3 Normal Modal Logics
12.4 Epistemic Logic for Multiagent Systems
12.5 Pro-attitudes: Goals and Desires
12.6 Common and Distributed knowledge
12.7 Integrated Theories of Agency
12.8Formal Methods in Agent-Oriented Software Engineering
12.8.1 Formal methods in specification
12.8.2 Formal methods in implementation
12.8.3 V erification
Reference Information and Books
For more information on agent technology in general, see “Artificial Life and Agent Technology” and “Introduction to Multi-Agent Systems,” and for simulation applications, see “MAS (Multi-Agent Simulation System) by Pyhton.
For Semantic Web services, see “Modeling Semantic Web Services: The Web Service Modeling Language,
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