Towards Playing Full MOBA Games with Deep Reinforcement Learning.
Deheng YeGuibin ChenWen ZhangSheng ChenBo YuanBo LiuJia ChenZhao LiuFuhao QiuHongsheng YuYinyuting YinBei ShiLiang WangTengfei ShiQiang FuWei YangLanxiao HuangWei LiuPublished in: CoRR (2020)
Keyphrases
- reinforcement learning
- game playing
- computer games
- temporal difference learning
- games played
- game players
- foreign language learners
- imperfect information
- action sets
- learning agents
- online game
- board game
- multi player
- function approximation
- video games
- card game
- general game playing
- game tree search
- state space
- card games
- game theoretic
- model free
- reinforcement learning agents
- educational games
- computer poker
- human players
- game play
- game theory
- two player games
- game design
- dynamic programming
- opponent modeling
- optimal policy
- playing games
- perfect information
- action selection
- nash equilibrium
- learning process
- game tree
- markov decision processes
- minimax search
- multiagent learning
- markov decision process
- role playing game
- coalitional games
- game development
- deep learning
- nash equilibria
- neural network
- digital games
- reinforcement learning algorithms
- game based learning
- cooperative
- multi agent
- learning algorithm
- machine learning