By Angel Kuri-Morales, Edwin Aldana-Bobadilla (auth.), Félix Castro, Alexander Gelbukh, Miguel González (eds.)
The two-volume set LNAI 8265 and LNAI 8266 constitutes the lawsuits of the twelfth Mexican foreign convention on synthetic Intelligence, MICAI 2013, held in Mexico urban, Mexico, in November 2013. the complete of eighty five papers provided in those lawsuits have been rigorously reviewed and chosen from 284 submissions. the 1st quantity bargains with advances in man made intelligence and its purposes and is dependent within the following 5 sections: common sense and reasoning; knowledge-based structures and multi-agent platforms; common language processing; desktop translation and bioinformatics and scientific functions. the second one quantity bargains with advances in tender computing and its purposes and is based within the following 8 sections: evolutionary and nature-inspired metaheuristic algorithms; neural networks and hybrid clever platforms; fuzzy platforms; computing device studying and trend acceptance; facts mining; machine imaginative and prescient and photograph processing; robotics, making plans and scheduling and emotion detection, sentiment research and opinion mining.
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Extra resources for Advances in Soft Computing and Its Applications: 12th Mexican International Conference on Artificial Intelligence, MICAI 2013, Mexico City, Mexico, November 24-30, 2013, Proceedings, Part II
LNCS, vol. 542, pp. 409–418. Springer, Heidelberg (1991) 12. : Self-Adaptation in Genetic Algorithms. , Bourgine, P. ) Toward a Practice of Autonomous Systems: Proceedings of the First European Conference on Artificial Life, pp. 263–271. MIT Press (1991) 13. : Evolutionary Algorithms in Theory and Practice. Oxford University Press (1996) 14. : An Analysis of the Behavior of a Class of Genetic Adaptive Systems. Doctoral Dissertation, University of Michigan (1975) 15. : An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms.
The original idea is to estimate a fraction of the population each generation. For the sake of this article, let α be the fraction of the population that is estimated, therefore, randomly chosen αN individuals will inherit their evaluations from their parents. In the work of Smith , the average of parents ﬁtness is proposed as a good estimator of child ﬁtness. Also, the weighted sum of ﬁtness, based on cross-point, is proposed in that report. Expressions for both ways of inheritance estimation appear in equations 1 and 2.
95 1 Fig. 1. An example of expected relationship between absolute-mean error and mean conﬁdence for a inheritance-based GA. The samples are taken from the results of 10 diﬀerent runs. From the graph can be inferred some negative relationship between the variables. 88. 1 A Model of Conﬁdence It is possible to modify an inheritance-based GA to perform conﬁdence estimation and then investigate the eﬀects of uncertainty, even if conﬁdence itself is not used in someway to control the process. It is possible to derive an equation of the evolution of mean population conﬁdence during runtime by realizing the following facts: – – – – Evaluated individual have a conﬁdence of 1.
Advances in Soft Computing and Its Applications: 12th Mexican International Conference on Artificial Intelligence, MICAI 2013, Mexico City, Mexico, November 24-30, 2013, Proceedings, Part II by Angel Kuri-Morales, Edwin Aldana-Bobadilla (auth.), Félix Castro, Alexander Gelbukh, Miguel González (eds.)