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Explainable and Interpretable Reinforcement Learning for Robotics

Produktform: Buch / Einband - fest (Hardcover)

 The authors consider classification techniques used in past surveys and papers and attempt to unify terminology across the field. The book provides an in-depth exploration of 12 attributes that can be used to classify explainable/interpretable techniques. These include whether the RL method is model-agnostic or model-specific, self-explainable or post-hoc, as well as additional analysis of the attributes of scope, when-produced, format, knowledge limits, explanation accuracy, audience, predictability, legibility, readability, and reactivity. The book is organized around a discussion of these methods broken down into 42 categories and subcategories, where each category can be classified according to some of the attributes. The authors close by identifying gaps in the current research and highlighting areas for future investigation. weiterlesen

Dieser Artikel gehört zu den folgenden Serien

Sprache(n): Englisch

ISBN: 978-3-031-47517-7 / 978-3031475177 / 9783031475177

Verlag: Springer International Publishing

Erscheinungsdatum: 20.03.2024

Seiten: 114

Auflage: 1

Autor(en): Ram D. Sriram, Dinesh Manocha, Aaron M. Roth, Ram Sriram, Elham Tabassi

58,84 € inkl. MwSt.
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