Reinforcement Learning, Bit by Bit

af Xiuyuan Lu

Reinforcement learning agents have demonstrated remarkable achievements in simulated environments. Data efficiency, however, significantly impedes carrying this success over to real environments. The design of data-efficient agents that address this problem calls for a deeper understanding of information acquisition and representation. This tutorial offers a framework that can guide associated agent design decisions. This framework is inspired in part by concepts from information theory that has... (Læs mere)