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Reinforcement learning assignments covering bandits, tabular RL, deep RL, and DQN variants. Includes implementations of ε-greedy and Thompson sampling bandits, SARSA/Expected SARSA on FrozenLake, Q-learning and Actor–Critic with neural networks, and an applied project evaluating DQN extensions for ICU sepsis treatment.
This repository contains a Reinforcement Learning framework for reliable routing in stochastic graphs, utilizing Q-Learning and advanced graph pruning techniques (Arc-Flags, Reach) to optimize SOTA (Stochastic On-Time Arrival) pathfinding under time-budget constraints.