| 書目名稱 | General Game Playing | | 編輯 | Michael Genesereth,Michael Thielscher | | 視頻video | http://file.papertrans.cn/383/382051/382051.mp4 | | 叢書名稱 | Synthesis Lectures on Artificial Intelligence and Machine Learning | | 圖書封面 |  | | 描述 | General game players are computer systems able to play strategy games based solely on formal game descriptions supplied at "runtime" (n other words, they don‘t know the rules until the game starts). Unlike specialized game players, such as Deep Blue, general game players cannot rely on algorithms designed in advance for specific games; they must discover such algorithms themselves. General game playing expertise depends on intelligence on the part of the game player and not just intelligence of the programmer of the game player. GGP is an interesting application in its own right. It is intellectually engaging and more than a little fun. But it is much more than that. It provides a theoretical framework for modeling discrete dynamic systems and defining rationality in a way that takes into account problem representation and complexities like incompleteness of information and resource bounds. It has practical applications in areas where these features are important, e.g., in business andlaw. More fundamentally, it raises questions about the nature of intelligence and serves as a laboratory in which to evaluate competing approaches to artificial intelligence. This book is an elementar | | 出版日期 | Book 2014 | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-01569-4 | | isbn_softcover | 978-3-031-00441-4 | | isbn_ebook | 978-3-031-01569-4Series ISSN 1939-4608 Series E-ISSN 1939-4616 | | issn_series | 1939-4608 | | copyright | Springer Nature Switzerland AG 2014 |
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