Stefano Del Col

Reward-Free Policy Space Compression for Reinforcement Learning

In reinforcement learning, we encode the potential behaviors of an agent interacting with an environment into an infinite set of policies, called policy space, typically represented by a family of parametric functions. Dealing with such a policy space is a hefty challenge, which often causes sample…