Open-ended learning in symmetric zero-sum games
Balduzzi et al.: http://proceedings.mlr.press/v97/balduzzi19a.html
#ArtificialIntelligence #MachineLearning #Nash #GameTheory
Balduzzi et al.: http://proceedings.mlr.press/v97/balduzzi19a.html
#ArtificialIntelligence #MachineLearning #Nash #GameTheory
PMLR
Open-ended learning in symmetric zero-sum games
Zero-sum games such as chess and poker are, abstractly, functions that evaluate pairs of agents, for example labeling them ‘winner’ and ‘loser’. If the game ...