Background: Reinforcement Learning enables the agent finishing several different tasks in unknown environments. Algorithmic Game Theory aims at finding good strategy for each agent in a multi-agent system under certain rules.

Key Techniques: Conterfactual Regret Minimization, Thompson Sampling, Nash Equilibrium Finding, Model-based Reinforcement Learning, Combo Action.