Marcus Vinícius C. Baldo

This paper introduces a computational framework for analyzing repeated binary choice experiments, revealing hidden decision patterns through advanced time series analysis methods.

The paper uses reinforcement learning to analyze why humans probability match instead of maximize in a learning task, finding that pattern search, exploration, and recency significantly influence behavior.