MICo: Improved representations via sampling-based state similarity for Markov decision processes Pablo Samuel Castro

We present a new behavioural distance over the state space of a Markov decision process, and demonstrate the use of this distance as an effective means of shaping the learnt representations of deep reinforcement learning agents.