Rock paper scissors against a Hedge ensemble that learns your habits — beats patterned players 80-100% while correctly settling at chance against true randomness.
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Updated
Aug 20, 2026 - JavaScript
Rock paper scissors against a Hedge ensemble that learns your habits — beats patterned players 80-100% while correctly settling at chance against true randomness.
This rep contains the projects made for the course "Reinforcement Learning and Dynamic Optimization" at TUC (2024).
Solver for repeated payoff-matrix games that adapts to non-stationary opponents.
CPU-first experiments on predictive correspondences between adaptive dynamical systems
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