"Distributional reinforcement learning provides a mathematical theory to describe the random outcomes caused by an agent's decisions"--Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Marc G. Bellemare is Senior Staff Research Scientist, Google Research and Adjunct Professor, McGill University. Will Dabney is Senior Staff Research Scientist, DeepMind. Mark Rowland is Senior Research Scientist, DeepMind.
Inhaltsangabe
Preface ix 1 Introduction 1 2 The Distribution of Returns 11 3 Learning the Return Distribution 51 4 Operators and Metrics 77 5 Distributional Dynamic Programming 115 6 Incremental Algorithms 161 7 Control 197 8 Statistical Functionals 233 9 Linear Function Approximation 261 10 Deep Reinforcement Learning 293 11 Two Applications and a Conclusion 319 Notation 333 References 337 Index 365
Preface ix 1 Introduction 1 2 The Distribution of Returns 11 3 Learning the Return Distribution 51 4 Operators and Metrics 77 5 Distributional Dynamic Programming 115 6 Incremental Algorithms 161 7 Control 197 8 Statistical Functionals 233 9 Linear Function Approximation 261 10 Deep Reinforcement Learning 293 11 Two Applications and a Conclusion 319 Notation 333 References 337 Index 365
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