Before revision: We propose two algorithms for episodic stochastic shortest path problems with linear function approximation. The first is computationally expensive but provably obtains (\sqrt{B_\star^3 d^3 K/c_{min , where B_\star is a (known)upper bound on the optimal cost-to-go function, d is the feature dimension, K is the number of episodes, and c_{min .
After revision: We propose two algorithms for episodic stochastic shortest path (\sqrt{B_\star^3 d^3 K/c_{min , where B_\star is a (known)upper bound on the optimal cost-to-go function, d is the feature dimension, K is the number of episodes, and c_{min .