From the Publisher:
This is the first comprehensive introduction to multiagent systems and contemporary distributed artificial intelligence. The book provides detailed coverage of basic topics as well as several closely related ones and is suitable as a textbook. The book can be used for teaching as well as self-study, and it is designed to meet the needs of both researchers and practitioners. In view of the interdisciplinary nature of the field, it will be a useful reference not only for computer scientists and engineers, but for social scientists and management and organization scientists as well.

Multiagent Systems : A Modern Approach to Distributed Artificial Intelligence

Automated negotiation systems with self interested agents are becoming increas ingly important One reason for this is the technology push of a growing standardized communication infrastructure Internet WWW NII EDI KQML FIPA Concor dia Voyager Odyssey Telescript Java etc over which separately designed agents belonging to di erent organizations can interact in an open environment in real time and safely carry out transactions The second reason is strong application pull for computer support for negotiation at the operative decision making level For example we are witnessing the advent of small transaction electronic commerce on the Internet for purchasing goods information and communication bandwidth There is also an industrial trend toward virtual enterprises dynamic alliances of small agile enterprises which together can take advantage of economies of scale when available e g respond to more diverse orders than individual agents can but do not su er from diseconomies of scale Multiagent technology facilitates such negotiation at the operative decision mak ing level This automation can save labor time of human negotiators but in addi tion other savings are possible because computational agents can be more e ective at nding bene cial short term contracts than humans are in strategically and com binatorially complex settings This chapter discusses multiagent negotiation in situations where agents may have di erent goals and each agent is trying to maximize its own good without concern for the global good Such self interest naturally prevails in negotiations among independent businesses or individuals In building computer support for negotiation in such settings the issue of self interest has to be dealt with In cooperative distributed problem solving the system designer imposes an interaction protocol and a strategy a mapping from state history to action a

Distributed rational decision making

Market mechanisms such as auctions will likely rep resent a common interaction medium for agents on the Internet The Michigan Internet AuctionBot is a ex ible scalable and robust auction server that supports both software and human agents The server manages many simultaneous auctions by separating the interface from the core auction procedures This design provides a responsive interface and tolerates system and network disruptions but necessitates careful timekeeping proce dures to ensure temporal accuracy The AuctionBot has been used extensively in classroom exercises and is available to the general Internet population Its exi ble speci cation of auctions in terms of orthogonal pa rameters makes it a useful device for agent researchers exploring the design space of auction mechanisms

The Michigan Internet AuctionBot: a configurable auction server for human and software agents

Different driving forces push the electricity production towards decentralization. As a result, the current electricity infrastructure is expected to evolve into a network of networks, in which all system parts communicate with each other and influence each other. Multi-agent systems and electronic markets form an appropriate technology needed for control and coordination tasks in the future electricity network. We present the PowerMatcher, a market-based control concept for supply and demand matching (SDM) in electricity networks. In a presented simulation study is shown that the simultaneousness of electricity production and consumption can be raised substantially using this concept. Further, we present a field test with medium-sized electricity producing and consuming installations controlled via this concept, currently in preparation.

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PowerMatcher: multiagent control in the electricity infrastructure

A multi-agent system for energy management of distributed power sources

Power load management enables energy utilities to reduce peak loads and thereby save money. Due to the large number of different loads, power load management is a complicated optimization problem. We present a new decentralized approach to this problem by modeling direct load management as a computational market. Our simulation results demonstrate that our approach is very efficient with a superlinear rate of convergence to equilibrium and an excellent scalability, requiring few iterations even when the number of agents is in the order of one thousand. Aframework for analysis of this and similar problems is given which shows how nonlinear optimization and numerical mathematics can be exploited to characterize, compare, and tailor problem-solving strategies in market-oriented programming.

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Power Load Management as a Computational Market

Power load management enables energy utilities to reduce peak loads and thereby save money. Due to the large number of different loads, power load management is a complicated optimization problem. We present a new decentralized approach to this problem by modeling direct load management as a computational market. Our simulation results demonstrate that our approach is very efficient with a superlinear rate of convergence to equilibrium and an excellent scalability, requiring few iterations even when the number of agents is in the order of one thousand. A framework for analysis of this and similar problems is given which shows how nonlinear optimization and numerical mathematics can be exploited to characterize, compare and tailor problem-solving strategies in market-oriented programming.

The deregulation of the European energy market, combined with emerging advanced capabilities of information technology, provides strategic opportunities for new knowledge-oriented services on the power grid. HOMEBOTS is the name we have coined for one of these innovative services: decentralized power load management at the customer side, automatically carried out by a 'society' of interactive household, industrial and utility equipment. They act as independent intelligent agents that communicate and negotiate in a computational market economy. The knowledge and competence aspects of this application are discussed, using an improved version of task analysis according to the COMMONKADS knowledge methodology. Illustrated by simulation results, we indicate how customer knowledge can be mobilized to achieve joint goals of cost and energy savings. General implications for knowledge creation and its management are discussed.

HOMEBOTS : Intelligent Decentralized Services for Energy Management

Multi-Agent Systems (MAS) promise to offer solutions to problems where established, older paradigms fall short. To be able to keep promises, however, indepth studies of advantages and weaknesses of MAS solutions versus conventional ones in practical applications are needed. In this paper we offer one such study. Climate control in large buildings is one application area where MAS, and market-oriented programming in particular, have been reported to be very successful. We have therefore constructed and implemented a variety of market designs for this problem, as well as different standard control engineering solutions. This paper gives a detailed analysis and comparison, so as to learn about differences between standard versus MAS approaches, and yielding new insights about benefits and limitations of computational markets.

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Fredrik Ygge

Papers

Power Load Management as a Computational Market

Power Load Management as a Computational Market

HOMEBOTS : Intelligent Decentralized Services for Energy Management

Making a Case for Multi-Agent Systems

Smart Software as Costumer Assistant in Large-Scale Distributed Load Management