A Unified Game-Theoretic Approach to Multi-agent Reinforcement Learning

Today we will dig into a paper ripped of A Unified Game-Theoretic Approach to Multi-agent Reinforcement Learning, one of the core ideas that has been used for the development of #AlphaStar . There are several concepts in AlphaStar that won t be treated here . The aim is to dig in the concepts that what has been as the "Nash League" conceptual functioning and how game theory came to mix with reinforcement learning . At the end of this article you should have a notion of Double Oracle algorithm, Deep Cognitive Hierarchies and Policy-Space Response Oracles . For this post you should be familiarized with some concepts about game theory, like the setup of the strategic game in form of the payoff matrix, the understanding of Nash Equilibria and best response.