Download Agent and Multi-Agent Systems: Technologies and by Michael Wooldridge (auth.), James O’Shea, Ngoc Thanh Nguyen, PDF

By Michael Wooldridge (auth.), James O’Shea, Ngoc Thanh Nguyen, Keeley Crockett, Robert J. Howlett, Lakhmi C. Jain (eds.)

This publication constitutes the refereed lawsuits of the fifth KES overseas convention on Agent and Multi-Agent structures, KES-AMSTA 2011, held in Manchester, united kingdom, in June/July 2011.
The sixty nine revised papers awarded have been conscientiously reviewed and chosen for inclusion within the booklet. additionally the amount comprises one summary and one complete paper size keynote speech. The papers are geared up in topical sections on conversational brokers, discussion structures and textual content processing; brokers and on-line social networks; robotics and production; agent optimisation; negotiation and safety; multi-agent structures; mining and profiling; agent-based optimization; doctoral song; computer-supported social intelligence for human interplay; electronic economic climate; and clever workflow, cloud computing and systems.

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Extra resources for Agent and Multi-Agent Systems: Technologies and Applications: 5th KES International Conference, KES-AMSTA 2011, Manchester, UK, June 29 – July 1, 2011. Proceedings

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Springer-Verlag Berlin Heidelberg 2011 36 M. Hijjawi et al. employed stemming for scripting or as a pre-processing stage. In addition, a little or no research has been done on conversational agents based on Arabic. Therefore, this paper is a subsequent work on developed conversational agent based on Arabic language. Over the years, a number of stemming approaches have been built for different languages including Arabic. However, an approach which might be useful for one language may not be useful for another due to the features differences among languages.

Measuring semantic similarity between words using lexical knowledge and neural networks. , Hubbard, S. ) IDEAL 2002. LNCS, vol. 2412, pp. 111–116. Springer, Heidelberg (2002) 25. : Sentence Similarity Based on Semantic Nets and Corpus Statistics. IEEE Transactions on Knowledge and Data Engineering 18(8), 1138–1150 (2006) 26. : An approach for Measuring Semantic Similarity Between Words Using Multiple Information Sources. IEEE Transactions on Knowledge and Data Engineering 15(4), 871–881 (2003) 27.

Baldassarre, G. ) ABiALS 2006. LNCS (LNAI), vol. 4520, pp. 108–127. Springer, Heidelberg (2007) 45. : Learning automata as a basis for multi agent reinforcement learning. , Sen, S. ) LAMAS 2005. LNCS (LNAI), vol. 3898, pp. 71–85. Springer, Heidelberg (2006) 46. : Learning and revising user profiles: the identification of interesting web sites. Mach. Learn. 27(3), 313–331 (1997) 47. : A generic architecture for adaptive agents based on reinforcement learning. Inf. Sc. 161, 37–55 (2004) 48. : Meta-learning in Distributed Data Mining Systems: Issues and Approaches.

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