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What is Self-Tuning EWA in Game Learning about?

This document presents a self-tuning experience weighted attraction (EWA) model of learning in games. The model addresses issues with cross-game variation in learning parameters and predicts behavior in new games without pre-specifying parameters. It is tested on several games and found to outperform equilibrium and non-self-tuning models by adding the most economic value in helping players earn more.

Author

Sujit Sekhar

Language

EN