Policy Gradient

Reinforcement Learning for Dynamic Bet Timing and Execution

How to frame autonomous bet timing as a reinforcement learning problem — MDPs, Q-learning, DQN, policy gradients, sim-to-real transfer, and combining RL execution with model-based edge detection.