graph-paths

This paper introduces Stochastic Reset Pathfinding (SRP), an episodic learning problem on a known directed graph with unknown stationary edge success probabilities, where failures reset the agent to the source. The authors propose PathUCB and PathTS algorithms with path-level regret bounds and demonstrate empirical performance across several domains.