Game AI and imperfect-information modelling
Regret-Based Reinforcement Learning in Poker
A quantitative development case study implementing Extensive-form Regret Minimisation in Python and PySpiel, validating poker strategies against OpenSpiel baselines, and analysing exploitability.
Methods: quant developer, poker AI, reinforcement learning, regret minimisation, OpenSpiel, Python, game theory.
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