MP Wellman, J Estelle, S Singh, Y Vorobeychik, C Kiekintveld, and V Soni

Computational Intelligence 21(1):1-26, 2005.
Copyright (c) 2005, Blackwell Publishing


The TAC supply-chain game presented automated trading agents with a challenging strategic problem. Embedded within a high-dimensional stochastic environment was a pivotal strategic decision about initial procurement of components. Early evidence suggested that the entrant field was headed toward a self-destructive, mutually unprofitable equilibrium. Our agent, Deep Maize, introduced a preemptive strategy designed to neutralize aggressive procurement, perturbing the field to a more profitable equilibrium. It worked. Not only did preemption improve Deep Maize’s profitability, it improved profitability for the whole field. Whereas it is perhaps counterintuitive that actions designed to prevent others from achieving their goals actually helps them, strategic analysis employing an empirical game-theoretic methodology verifies and provides insight about this outcome.

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