A novel method for strategy acquisition and its application to a double-auction market game

We introduce a method for strategy acquisition in nonzero-sum n -player games and empirically validate it by applying it to a well-known benchmark problem in this domain, namely, the double-auction market. Many existing approaches to strategy acquisition focus on attempting to find strategies that are robust in the sense that they are good all-round performers against all-comers. We argue that, in many economic and multiagent scenarios, the robustness criterion is inappropriate; in contrast, our method focuses on searching for strategies that are likely to be adopted by participating agents, which is formalized as the size of a strategy's basins of attraction under the replicator dynamics.