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Titlebook: Qualitative Spatial Abstraction in Reinforcement Learning; Lutz Frommberger Book 2010 Springer-Verlag Berlin Heidelberg 2010 Spatial Abstr

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樓主: DUBIT
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發(fā)表于 2025-3-25 06:04:24 | 只看該作者
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發(fā)表于 2025-3-25 19:43:01 | 只看該作者
Summary and Outlook,This chapter concludes this book with a summary and discussion of the presented work and an outlook on future research based on the described results.
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發(fā)表于 2025-3-25 22:29:07 | 只看該作者
Lutz FrommbergerBook introduces many original ideas.Significant contribution to the field of reinforcement learning.Contains pointers to future research
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發(fā)表于 2025-3-26 00:52:28 | 只看該作者
1611-2482 nforcement learning has developed as a successful learning approach for domains that are not fully understood and that are too complex to be described in closed form. However, reinforcement learning does not scale well to large and continuous problems. Furthermore, acquired knowledge specific to the
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發(fā)表于 2025-3-26 12:14:48 | 只看該作者
Qualitative State Space Abstraction,. 4.1) and presents a formal framework of abstraction and its different facets in Sect. 4.2. Based on this framework, a view on the interdependence of abstraction and representation follows in Sect. 4.3. Section 4.4 examines abstraction in agent control processes before applying them to reinforcemen
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