"Babes-Bolyai" University of Cluj-Napoca
Faculty of Mathematics and Computer Science
| Evolutionary Computing in Artificial Intelligence |
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| Teaching Staff in Charge |
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| Aims |
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The basic paradigms, techniques and algorithms of Evolutionary computing are presented
The relationship of Evolutionary Computing and Artificial Intelligence is investigated. |
| Content |
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1. Evolutionary Computing . Evolutionary algortithms, mainstreams of EC
2. Genetic algorithms, binary representation, search operators, population models, basic GA 3. Learning machines, basic LM techniques 4. Decision trees, binary DT, generalized DT, evolutionary design of DT 5. Evolutionary clustering, one level clustering, hierarchical clustering, dynamic clustering 6. Evolutionary pattern recognition 7. Evolutionary learning in AI 8. Evolutionary neural network, evolutionary design of NN |
| References |
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DUMITRESCU,D.,B Lazzerini,Evolutionary Computation, CRC Press, New York, Boca Raton, 2000
DUMITRESCU,D.,B Lazzerini,Fuzzy Sets and treir Application in Training and Clustering , CRC Press, New York, Boca Raton, 2000 DUMITRESCU, D.,Principiile Inteligentei artificiale, Editura Albastra, Cluj,2000. DUMITRESCU, D.,Principiile teoriei clasificarii, Editura Academiei, Bucuresti,2000. DUMITRESCU, D.,Algoritmi genetici si strategii evolutive. Aplicatii in Inteligenta Artificiala, Editura Albastra, Cluj,2000. DUMITRESCU, D., Inteligenta artificiala, Univ. "Babes-Bolyai", 1995. DUMITRESCU, D., Modele conexioniste in Inteligenta Artificiala, Univ. "Babes-Bolyai", 1995. DUMITRESCU, D., Retele Neuronale, Teora, 1997 GOLDBERG, D. E., Genetic Algorithms in Search, Optimization , and Machine Learning, Addison , Reading, 1989. MICHALEVICZ, Z., Genetic Algorithms + Data Structures = Evolution Programs, Springer, Berlin, 1992. |
| Assessment |
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continuous examination, small project |