Achievement
Deviation-preserving reduction method
Project
IGERT: Incentive-Centered Design for Information and Communication Systems
University
University of Michigan at Ann Arbor
(Ann Arbor, MI)
PI
Trainee Achievements
Deviation-preserving reduction method
IGERT fellow, Bryce Wiedenbeck, is the lead author in a refereed conference proceeding in Computer Science:
Wiedenbeck, B., and Wellman, M.P. (2012, June). Scaling Simulation-based Game Analysis through Deviation-Preserving Reduction. 11th International Conference on Autonomous Agents and Multiagent Systems, Valencia, Spain, pp. 931-938.
Multiagent simulation extends the reach of game-theoretic analysis to scenarios where payoff functions can be computed from implemented agent strategies. However this approach is limited by the exponential growth in game size relative to the number of agents. Player reductions allow us to construct games with a small number of players that approximate very large symmetric games. We introduce deviation-preserving reduction, which generalizes and improves on existing methods by combining sensitivity to unilateral deviation with granular subsampling of the profile space. We evaluate our method and demonstrate its superiority over prior methods.
- “Trainee Achievements”
- Achievements for this Project