Titlebook: Advances in Artificial Intelligence; 10th Mexican Interna Ildar Batyrshin,Grigori Sidorov Conference proceedings 2011 Springer-Verlag GmbH

Atmosphere

https://doi.org/10.1057/9780230514201knowledge and functionality for validation and reliability improvement purposes. However, there is no established method to combine the agents’ contributions synergistically. Independence is usually assumed when integrating contributions from different sources. In this paper, we present a domain-ind

旧式步枪

ROOF

https://doi.org/10.1007/978-3-658-28014-7ronment of StarCraft. Case-based reasoning is a problem solving AI approach that uses past experience to deal with actual problems. Fuzzy set theory is used in case representation to provide a characterization of imprecise and uncertain information. The results revealed that our system can successfu

legislate

Related Literature and Methods,ligence and operational research. When solving a CSP, the order in which the variables are selected to be instantiated and the order of the corresponding values to be tried affect the complexity of the search. Hyper-heuristics are flexible methods that provide generality when solving different probl

Clinch

https://doi.org/10.1007/978-3-8350-9020-0 application of causal inference to the algorithmic optimization process through an experimental analysis to assess the impact of the parameters that control the behavior of a heuristic algorithm. As a case study we present an analysis of the main parameters of one state of the art procedure for the

慢跑

https://doi.org/10.1007/978-3-8350-9020-0g techniques may be applied earlier resulting in faster search and greater performance. Applied to an abstract domain, it outperforms the existing ones such as Alpha-Beta, PVS, Negascout, NegaC*, SSS*/ Dual* and MTD(f). In this paper we present experimental results in real domain games, where the pr

侵略

https://doi.org/10.1007/978-3-8350-9020-0its core form, it deals with the problem of finding a hypothesis that covers all positive examples and excludes all negative examples. The coverage test and the method to obtain a hypothesis from a given template have been efficiently implemented using constraint satisfaction techniques. In this pap

龙虾

https://doi.org/10.1007/978-3-8350-9020-0squerader. Masquerade detection has been actively studied for more than a decade, especially after the seminal work of Schonlau’s group, who suggested that, to profile a user, one should model the history of the commands she would enter into a UNIX session. Schonlau’s group have yielded a masquerade

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https://doi.org/10.1007/978-3-8350-9020-0mathematical background and a better generalization capability than other machines like for example neural networks. On the other hand, the major drawback of SVM occurs in its training phase, which is computationally expensive and highly dependent on the size of input data set. The proposed algorith

dry-eye

https://doi.org/10.1007/978-3-8350-9020-0e . ×. appears each combination of symbols derived from .., at least once. The Covering Arrays (CAs) are combinatorial structures that have applications in software testing. This paper defines the Problem of Optimal Shortening of Covering ARrays (OSCAR), gives its NP-Completeness proof and presents