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Chapter 30MULTI-AGENT CONTRACT NEGOTIATIONKnowledge and Computation ComplexitiesPeyman FaratinMIT Sloan School of ManagementAbstractTwo computational decision models are presented for the problem of de-centralizedcontracting of multi-dimensional services and goods between autonomousagents. The assumption of the models is that agents are bounded in both informationand computation. Heuristic and approximate solution techniques fromArtificial Intelligence are used for the design of decision mechanism that approachmutual selection of efficient contracts.1. IntroductionThe problem of interest in this chapter is how autonomous computationalagents can approach an efficient trading of multi-dimensional services or goodsunder assumptions of bounded rationality. Trading is assumed to involve negotiation,a resolution mechanism for conflicting preferences between selfishagents. We restrict ourselves to a monopolistic economy of two trading agentsthat meet only once to exchange goods and services. Agents are assumed to bebounded in both information and computation. Information needed for decisionmaking is assumed to be bounded due to both external and internal factors, socialand local information respectively. Agents have limited social informationbecause they are assumed to be selfish, sharing little or no information. In additionto this agents may also have limited local information (for example overtheir own preferences) because of complexity of their local task(s). Computation,in turn, is a problem in contract negotiation because of the combinatoricsof scale. Computation is informally defined as the process of searching a spaceof possibilities [11]. For a contract with ½¼¼ issues and only two alternativesfor each issue, the size of the search space is roughly ½¼ ¿¼ possible contracts,too large to be explored exhaustively.