Promoting human-AI interaction makes a better adoption of deep reinforcement learning: a real-world application in game industry.
Zhipeng HuHaoyu LiuYu XiongLizi WangRunze WuKai GuanYujing HuTangjie LyuChangjie FanPublished in: Multim. Tools Appl. (2024)
Keyphrases
- reinforcement learning
- human interaction
- artificial intelligence
- human robot
- human interactions
- human players
- case study
- virtual characters
- electronic data interchange
- human robot interaction
- machine learning
- game theoretic
- state space
- game theory
- protein interaction
- human intelligence
- function approximation
- agent learns
- game ai
- sensory inputs
- human communication
- human operators
- action selection
- artificially intelligent
- user interaction
- learning algorithm
- optimal policy
- computer games
- video games
- serious games
- cognitive psychology
- markov decision processes
- software industry
- game playing
- small businesses
- human level
- competitive market
- game design
- adoption decisions
- multi agent
- expert systems
- dynamic programming
- game players
- knowledge representation
- intelligent systems
- computational systems
- human computer interaction
- cognitive process
- model free
- human users