Stronger CDA strategies through empirical game-theoretic analysis and reinforcement learning

@inproceedings{Schvartzman2009StrongerCS,
  title={Stronger CDA strategies through empirical game-theoretic analysis and reinforcement learning},
  author={L. Julian Schvartzman and Michael Paul Wellman},
  booktitle={AAMAS},
  year={2009}
}
We present a general methodology to automate the search for e quilibrium strategies in games derived from computational exp erimentation. Our approach interleaves empirical game-theoreti c analysis with reinforcement learning. We apply this methodolog y to the classic Continuous Double Auction game, conducting the most comprehensive CDA strategic study published to date. Empir ical game analysis confirms prior findings about the relative perf ormance of known strategies. Reinforcement learning… CONTINUE READING

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