Computer automation has the potential, just starting to be realized, of transforming the design and operation of markets, and the behaviors of agents trading in them. We discuss the possibilities for automating markets, presenting a broad conceptual framework covering resource allocation as well as enabling marketplace services such as search and transaction execution. One of the most intriguing opportunities is provided by markets implementing computationally sophisticated negotiation mechanisms, for example combinatorial auctions. An important theme that emerges from the literature is the centrality of design decisions about matching the domain of goods over which a mechanism operates to the domain over which agents have preferences. When the match is imperfect (as is almost inevitable), the market game induced by the mechanism is analytically intractable, and the literature provides an incomplete characterization of rational bidding policies. A review of the literature suggests that much of our existing knowledge comes from computational simulations, including controlled studies of abstract market designs (e.g., simultaneous ascending auctions), and research tournaments comparing agent strategies in a variety of market scenarios. An empirical game-theoretic methodology combines the advantages of simulation, agent-based modeling, and statistical and game-theoretic analysis.
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ReDIF This chapter was published in: Leigh Tesfatsion & Kenneth L. Judd (ed.) Handbook of Computational Economics, , chapter 28, pages 1381-1431, 2006.
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This chapter was published in the following book, which is listed on IDEAS: Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006.
"Handbook of Computational Economics,"
Handbook of Computational Economics,
Elsevier,
edition 1, volume 2, number 2, September.
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