We present a general discussion of what constitutes a market‐oriented approach to optimization. We demonstrate how a general framework can be used to conceptually improve two well‐known approaches from the literature, and discuss computational properties of the different approaches. We also show how existing theory could be adjusted to be directly applicable to the theory of the two approaches, thus proving special theory unnecessary. We want to bring out the pedagogical aspects of market mechanisms, to take full advantage of its potential.

Supply chain formation presents difficult coordination issues for distributed negotiation protocols. Agents must simultaneously negotiate production relationships at multiple levels, with important interdependencies among inputs and outputs at each level. Combinatorial auctions address this problem by global optimization over expressed offers to engage in compound exchanges. A one-shot combinatorial auction that optimizes the reported value of the bids results in optimal allocations with truthful bids. But autonomous self-interested agents have an incentive to bid strategically in an attempt to gain extra surplus. We investigate a particular combinatorial protocol consisting of a one-shot auction and a strategic bidding policy. We experimentally analyze the efficiency and producer surplus obtained in five networks, and compare this performance to that of a distributed, progressive auction protocol with non-strategic bidding. We find that producers can sometimes gain significantly by bidding strategically. However, when the available surplus is small relative to the consumers ’ values, the producers’ strategic behavior may prevent the supply chain from forming at all, resulting in zero gains for all agents. We examine the robustness of the combinatorial protocol by investigating agent incentives to deviate, identifying quasi-equilibrium behavior for an example network. 1.

Multi-Agent Systems (MAS) promise to offer solutions to problems where established, older paradigms fall short. In order to validate such claims that are repeatedly made in software agent publications, empirical in-depth studies of advantages and weaknesses of multi-agent solutions versus conventional ones in practical applications are needed. Climate control in large buildings is one application area where multi-agent systems, and market-oriented programming in particular, have been reported to be very successful, although central control solutions are still the standard practice. We have therefore constructed and implemented a variety of market designs for this problem, as well as different standard control engineering solutions. This article gives a detailed analysis and comparison, so as to learn about differences between standard versus agent approaches, and yielding new insights about benefits and limitations of computational markets. An important outcome is that ``local information plus market communication produces global control''.