LEARNING
Reinforcement Learning Textbook
Sergey V. Ivanov
- 发表年份
- 2022
- 引用次数
- 5
- 访问权限
- 开放获取
摘要
This textbook covers principles behind main modern deep reinforcement learning algorithms that achieved breakthrough results in many domains from game AI to robotics. All required theory is explained with proofs using unified notation and emphasize on the differences between different types of algorithms and the reasons why they are constructed the way they are.
关键词
Reinforcement learningMathematical proofNotationArtificial intelligenceComputer scienceReinforcementCognitive scienceMathematicsPsychology
相关论文
OTHER
📊 26,957 引用
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 引用
Artificial intelligence: a modern approach
1995
OTHER
开放获取📊 20,501 引用
Fractional Differential Equations
Igor Podlubný
2025
OTHER
📊 18,993 引用
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991