Over Q-values is used to find actions close to Nash equilibrium. Variable that is used as part of the Q-value calculation. The second agent, Meta-Nash DQN,īuilds an implicit model of its opponent's policy in order to produce a context Response to exploit the opponent's strategy. Policy using imitation learning, and then uses this model to find the best The Best Response AgenT (BRAT), builds an explicit model of its opponent's Then we introduce two novel agents that attempt to handle theseĬhallenges by using joint action Deep Q-Networks (DQN). ![]() Sum simultaneous action games and discuss the unique challenges this type of Introduce the fundamental concepts of reinforcement learning in two player zero Two player zero sum simultaneous action games are common in video games,įinancial markets, war, business competition, and many other settings.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |