We derive optimal strategies for a bidding agent that participates in multiple, simultaneous second-price auctions with perfect substitutes. We prove that, if everyone else bids locally in a single auction, the global bidder should always place non-zero bids in all available auctions, provided there are no budget constraints. With a budget, however, the optimal strategy is to bid locally if this budget is equal or less than the valuation. Furthermore, for a wide range of valuation distributions, we prove that the problem of finding the optimal bids reduces to two dimensions if all auctions are identical. Finally, we address markets with both sequential and simultaneous auctions, non-identical auctions, and the allocative efficiency of the market.

A previous paper by D. Cliff (see ibid., 2002) demonstrated that a genetic algorithm could be used to automatically discover new optimal auction mechanisms for automated electronic marketplaces populated by software-agent traders. Significantly, the new auction mechanisms are often unlike traditional mechanisms designed by humans for human traders; rather, they are peculiar hybrid mixtures of established styles of mechanism. This previous work used software agents running the ZIP trader algorithm (recently shown to outperform human traders). We provide the first demonstration that qualitatively similar results (i.e., non-standard hybrid mechanism designs being optimal) are also given when similar experiments are performed using a different trader algorithm, namely Gode & Sunder's (1993) ZI-C traders. Thus, the paper is the first to offer significant evidence that evolved hybrid auction mechanisms may be found that out-perform traditional market mechanisms for many styles of trader-agent.

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Service composition is the act of taking several component products or services, and bundling them together to meet the needs of a given customer. In the future, service composition will play an increasingly important role in e-commerce, and automation will be desirable to improve speed and efficiency of customer response. In this paper, we consider a service composition agent that both buys components and sells services through auctions. It buys component services by participating in many English auctions. It sells composite services by participating in Request-for-Quotes reverse auctions. Because it does not hold a long-term inventory of component services, it must take risks; it must make offers in reverse auctions prior to purchasing all the components needed, and must bid in English auctions prior to having a guaranteed customer for the composite good. We present algorithms that is able to manage this risk, by appropriately bidding/offering in many auctions and reverse auctions simultaneously. The algorithms will withdraw from one set of possible auctions and move to another set if this will produce a better-expected outcome, but will effectively manage the risk of accidentally winning outstanding bids/offers during the withdrawal process. We illustrate the behavior of these algorithms through a set of worked examples.