Evolving bidding strategies for multiple auctions

Abstract

Due to the proliferation of online auctions, there is an increasing need to monitor and bid in multiple auctions in order to procure the best deal for the desired good. Against this background, this paper reports on the development of a heuristic decision making framework that an autonomous agent can exploit to tackle the problem of bidding across multiple auctions with varying protocols (including English, Dutch and Vickrey). The framework is flexible, configurable and enables the agent to adopt varying tactics and strategies that attempt to ensure the desired item is delivered in a manner consistent with the user's preferences. In this context, however, the best strategy for an agent to use is very much determined by the nature of the environment and by the user's preferences. Given this large space of possibilities, we employ a genetic algorithm to search (offline) for effective strategies in common classes of environment. The strategies that emerge from this evolution are then codified into the agent's reasoning behaviour so that it can select the most appropriate strategy to employ in its prevailing circumstances.

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