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Titlebook: Knowledge Engineering Tools and Techniques for AI Planning; Mauro Vallati,Diane Kitchin Book 2020 Springer Nature Switzerland AG 2020 Arti

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21#
發(fā)表于 2025-3-25 03:33:15 | 只看該作者
Maurício C. Magnaguagno,Ramon Fraga Pereira,Martin D. Móre,Felipe Meneguzzi
22#
發(fā)表于 2025-3-25 07:33:15 | 只看該作者
23#
發(fā)表于 2025-3-25 15:18:28 | 只看該作者
24#
發(fā)表于 2025-3-25 17:50:36 | 只看該作者
KEPS Book: Planning.DomainsIn this chapter we describe the main pillars of the Planning.Domains initiative (API, Solver, Editor, and Education), detail some of the current use-cases for them, and outline the future path of the initiative. We further dive into some of the most recent developments of Planning.Domains, and shed light on what is next for the platform.
25#
發(fā)表于 2025-3-25 23:14:16 | 只看該作者
26#
發(fā)表于 2025-3-26 01:38:06 | 只看該作者
Mauro Vallati,Diane KitchinThere is no up-to-date book which covers this topic area, only a few scattered research/conference papers which address this topic.Chapters writen by International leaders from both industry and acade
27#
發(fā)表于 2025-3-26 05:35:50 | 只看該作者
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28#
發(fā)表于 2025-3-26 10:59:09 | 只看該作者
https://doi.org/10.1007/978-3-030-38561-3Artificial Intelligence; AI Planning & Scheduling; Model-Based Reasoning; Knowledge Engineering; Knowled
29#
發(fā)表于 2025-3-26 15:49:56 | 只看該作者
30#
發(fā)表于 2025-3-26 20:47:53 | 只看該作者
Automated Domain Model Learning Tools for Planning by human experts or automatically learned through the observation of some existing plans (behaviours). Encoding a domain model manually from experience and intuition is a very complex and time-consuming task, even for domain experts. This chapter investigates various classical and state-of-the-art
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