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Titlebook: KI 2007: Advances in Artificial Intelligence; 30th Annual German C Joachim Hertzberg,Michael Beetz,Roman Englert Conference proceedings 200

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書(shū)目名稱(chēng)KI 2007: Advances in Artificial Intelligence
副標(biāo)題30th Annual German C
編輯Joachim Hertzberg,Michael Beetz,Roman Englert
視頻videohttp://file.papertrans.cn/542/541636/541636.mp4
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: KI 2007: Advances in Artificial Intelligence; 30th Annual German C Joachim Hertzberg,Michael Beetz,Roman Englert Conference proceedings 200
描述The 30th Annual German Conference on Arti?cial Intelligence (KI-2007) took place in the University of Osnabru ¨ck, September 10–13, 2007. In this volume, you will ?nd papers or abstracts of its six invited talks, 25 full papers, and 21 posters. The full papers were selected from 81 submissions, resulting in an acceptance rate of 32%. AsusualataKIconference,anentiredaywasreservedfortargetedworkshops – ten of them this year – and two tutorials. They are not coveredin this volume, but the conference Web sitewww.ki2007.uos.de will keep providing information and references to their contents. Some topic clusters are apparent in the overall conference program, which re?ect recent trends in AI research, convolved with foci of work in Germany and Europe. Examples are learning and data mining, robotics and perception, knowledge representation and reasoning, planning and search – all of them including a healthy number of approaches dealing with uncertainty, contradiction, and incompleteness of knowledge. All in all, KI-2007 provided a cross section of modern AI research and application work. KI-2007 also constituted a “small anniversary,” being the 30th exemplar of its kind. The invited talk
出版日期Conference proceedings 2007
關(guān)鍵詞agents; artificial intelligence; cognition; emotion; intelligence; learning; machine learning; ontology; rob
版次1
doihttps://doi.org/10.1007/978-3-540-74565-5
isbn_softcover978-3-540-74564-8
isbn_ebook978-3-540-74565-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2007
The information of publication is updating

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Pinpointing in the Description Logic ,is not surprising since we can show that a given TBox may have exponentially many such minimal subsets. However, we can also show that the problem is not even output polynomial, i.e., unless P=NP, there cannot be an algorithm computing all such minimal sets that is polynomial in the size of its inpu
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Extending Markov Logic to Model Probability Distributions in Relational Domainssponding restrictions on processes for which models can be learned using standard methods and thus enables Markov logic networks to be practically applied to a far greater class of generative stochastic processes.
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Conference proceedings 2007ing a healthy number of approaches dealing with uncertainty, contradiction, and incompleteness of knowledge. All in all, KI-2007 provided a cross section of modern AI research and application work. KI-2007 also constituted a “small anniversary,” being the 30th exemplar of its kind. The invited talk
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