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 ...
New Frontiers of Automated Mechanism Design for Pricing and Auctions by Maria-Florina Balcan, @mldcmu, Tuomas Sandholm, Ellen Vitercik @csdatcmu
Learn more → https://mld.ai/y1m
Tutorial Video Part I: https://youtu.be/buK3KXZcGAI
Tutorial Video Part II: https://youtu.be/T8gaK4Yw4zI
#MechanismDesign #GameTheory #Tutorial #MachineLearning #Optimization #ML
Learn more → https://mld.ai/y1m
Tutorial Video Part I: https://youtu.be/buK3KXZcGAI
Tutorial Video Part II: https://youtu.be/T8gaK4Yw4zI
#MechanismDesign #GameTheory #Tutorial #MachineLearning #Optimization #ML
Google
EC19 New Frontiers of Automated Mechanism Design for Pricing and Auctions