By Marcus Randall, Elliot Tonkes (auth.), László Monostori, József Váncza, Moonis Ali (eds.)
This booklet constitutes the refereed court cases of the 14th overseas convention on business and Engineering functions of man-made Intelligence and Export platforms, IEA/AIE 2001, held in Budapest, Hungary in June 2001. The 104 papers provided have been conscientiously reviewed and chosen from a complete of one hundred forty submissions. The court cases supply topical sections on looking out, wisdom illustration, model-based reasoning, computing device studying, facts mining, delicate computing, evolutionary algorithms, allotted challenge fixing, export structures, development and speech reputation, imaginative and prescient language processing, making plans and scheduling, robotics, self reliant brokers, layout, keep watch over, production platforms, finance and company, software program engineering, and clever tutoring.
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Extra info for Engineering of Intelligent Systems: 14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2001 Budapest, Hungary, June 4–7, 2001 Proceedings
In the following, Section 1 contains details of the GEA system: The class hierarchy and the purpose of the classes. Section 2 describes GREDEA, an application of GEA. Finally in Section 3 a summary of present and future work is given. 1 The GEA System This section describes the GEA system in detail. It is explained how the idea of creating such a programming library came up. Then the implemented representation forms, their genetic operators and the evolutionary algorithms of the latest version are presented.
Fogarty, editors, Genetic Programming, Proceedings of EuroGP’2000, volume 1802 of LNCS, pages 193-208, Edinburgh, 15-16 Apr. 2000. Springer-Verlag. 14. M. Wall. GAlib - A C++ Library of Genetic Algorithm Components. edu/ga/. org Value Prediction in Engineering Applications G. Ziegler1 , Z. Palotai2 , T. Cinkler1 , P. Arat´ o2 , and A. hu/˜lorincz/ Budapest, Hungary Abstract. In engineering application heuristics are widely used for discrete optimization tasks. We report two cases (in Dense Wavelength Division Multiplexing and High Level Synthesis), where a recent “intelligent” heuristic (STAGE) performs excellently by learning a value-function of the states.
In the application described here, parametric L-systems are evolved, which introduce parallel rewriting to parametric words. The evolution of parametric L-systems requires two kinds of evolutionary algorithms: GAs are used to evolve the rewriting rules of the evolved L-system, and ESs are applied on the parameters of the L-systems. Because the shape of the generated image depends both on the rewriting rules and on the parameters, the representation can be divided into two important parts. The right sides of the rules are represented as strings while the parameters are described as vectors of real values.