Learnable evolution model: Difference between revisions

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{{Original research|date=September 2007}}

The '''Learnablelearnable Evolutionevolution Modelmodel''' ('''LEM''') is a novel, non-[[Darwinian]] methodology for [[evolutionary computation]] that employs [[machine learning]] to guide the generation of new individuals ([[candidate solution|candidate problem solution]]s). Unlike standard, Darwinian-type evolutionary computation methods that use random or semi-random operators for generating new individuals (such as [[mutation (genetic algorithm)|mutation]]s and/or [[genetic recombination|recombination]]s), LEM employs hypothesis generation and instantiation operators.

The [[hypothesis generation]] operator applies a machine learning program to induce descriptions that distinguish between high-[[fitness (biology)|fitness]] and low-fitness individuals in each consecutive [[population]]. Such descriptions delineate areas in the [[Candidate solution|search space]] that most likely contain the desirable solutions. Subsequently the instantiation operator samples these areas to create new individuals.

LEM has been modified from optimization ___domain to classification ___domain by augmented LEM with ID3 (February 2013 by M. Elemam Shehab, K. Badran, M. Zaki and Gouda I. Salama).

== ResearchSelected Groupsreferences ==

* {{citation |last1=Cervone |first1=P. |last2=Franzese |title=Machine Learning for the Source Detection of Atmospheric Emissions |journal=Proceedings of the 8th Conference on Artificial Intelligence Applications to Environmental Science, Code J1.7 |date=January 2010}}

*[http://www.mli.gmu.edu Machine Learning and Inference Laboratory at George Mason University]

*{{citation |last1=Wojtusiak |first1=J. |last2=Michalski |first2=R. S. |title=Proceedings of the 8th annual conference on Genetic and evolutionary computation |chapter=The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems |date=2006 |___location=Seattle, WA |doi=10.1145/1143997.1144197 |page=1281|isbn=978-1595931863 |citeseerx=10.1.1.72.2298 |s2cid=6133889 }}

*{{citation |last1=Wojtusiak, |first1=J., "|title=Initial Study on Handling Constrained Optimization Problems in Learnable Evolution Model," ''|journal=Proceedings of Thethe Graduate Student Workshop at Genetic and Evolutionary Computation Conference'', GECCO 2006, Seattle, WA, |date=July 8-128–12, 2006. }}

*{{citation |last1=Jourdan |first1=L. |last2=Corne |first2=D. |last3=Savic |first3=D. |last4=Walters |first4=G. |title=Evolutionary Multi-Criterion Optimization |chapter=Preliminary Investigation of the 'Learnable Evolution Model' for Faster/Better Multiobjective Water Systems Design |volume=3410 |pages=841–855 |year=2005|doi=10.1007/978-3-540-31880-4_58 |citeseerx=10.1.1.73.9653 |series=Lecture Notes in Computer Science |isbn=978-3-540-24983-2 }}

*{{citation |last1=Domanski, |first1=P. A., |last2=Yashar, |first2=D., |last3=Kaufman, |first3=K. and |last4=Michalski, |first4=R. S., "|title=An Optimized Design of Finned-Tube Evaporators Using the Learnable Evolution Model," ''|journal=International Journal of Heating, Ventilating, Air-Conditioning and Refrigerating Research'', |volume=10, 201-211,|pages=201–211 |date=April, 2004. }}

*{{citation |last1=Kaufman |first1=K. and |last2=Michalski |first2=R. S., "|title=Applying Learnable Evolution Model to Heat Exchanger Design," ''|journal=Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000) and Twelfth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-2000)'', Austin, TX, pp. 1014-1019,|pages=1014–1019 |year=2000. }}

*{{Cite book|last1=Cervone |first1=G. |last2=Michalski |first2=R. S. |last3=Kaufman |first3=K. A. |title=Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) |chapter=Experimental validations of the learnable evolution model |pages=1064–1071 |date=July 2000|volume=2 |doi=10.1109/CEC.2000.870765 |isbn=0-7803-6375-2 |s2cid=3149132 }}

*{{citation |last1=Michalski |first1=R. S., "|title=LEARNABLE EVOLUTION MODEL Evolutionary Processes Guided by Machine Learning," ''|journal=Machine Learning'' , |volume=38, pp 9-40,|pages=9–40 |year=2000 |doi=10.1023/A:1007677805582|doi-access=free }}

*{{citation |last1=Michalski, |first1=R .S., "|title=Learnable Evolution: Combining Symbolic and Evolutionary Learning," ''|journal=Proceedings of the Fourth International Workshop on [[Multistrategy]] Learning'' (MSL'98), Desenzano del Garda, Italy, pp. 14-20,|pages=14–20 |date=June 11-1311–13, 1998.}}

*{{citation |last1=H Yar|first1=M. |title=A survey on evolutionary computation: Methods and their applications in engineering |journal=Mod. Appl. Sci |pages=14–20 |date=June 11–13, 2016}}

[[Category:Evolutionary computation]]

== Selected References ==

*Wojtusiak, J. and Michalski, R.S., "The LEM3 Implementation of Learnable Evolution Model and Its Testing on [[complex function|Complex Function]] [[Optimization (mathematics)|Optimization]] Problems," ''Proceedings of Genetic and Evolutionary Computation Conference'', GECCO 2006, Seattle, WA, July 8-12, 2006.

*Wojtusiak, J., "Initial Study on Handling Constrained Optimization Problems in Learnable Evolution Model," ''Proceedings of The Graduate Student Workshop at Genetic and Evolutionary Computation Conference'', GECCO 2006, Seattle, WA, July 8-12, 2006.

*Jourdan, L., Corne, D., Savic, D. and Walters, G., "Preliminary Investigation of the ‘Learnable Evolution Model’ for Faster/Better Multiobjective Water Systems Design," ''Proceedings of The Third Int. Conference on Evolutionary Multi-Criterion Optimization'', EMO’05, 2005.

*Domanski, P. A., Yashar, D., Kaufman, K. and Michalski, R. S., "An Optimized Design of Finned-Tube Evaporators Using the Learnable Evolution Model," ''International Journal of Heating, Ventilating, Air-Conditioning and Refrigerating Research'', 10, 201-211, April, 2004.

*Kaufman K. and Michalski R.S., "Applying Learnable Evolution Model to Heat Exchanger Design," ''Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-2000) and Twelfth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-2000)'', Austin, TX, pp. 1014-1019, 2000.

*Cervone G., Michalski R.S., Kaufman K. A., "Experimental Validations of the Learnable Evolution Model," ''2000 Congress on Evolutionary Computation'', San Diego CA, pp 1064-1071, July 2000.

*Michalski R.S., "LEARNABLE EVOLUTION MODEL Evolutionary Processes Guided by Machine Learning," ''Machine Learning'' , 38, pp 9-40, 2000.

*Michalski, R.S., "Learnable Evolution: Combining Symbolic and Evolutionary Learning," ''Proceedings of the Fourth International Workshop on [[Multistrategy]] Learning'' (MSL'98), Desenzano del Garda, Italy, pp. 14-20, June 11-13, 1998.

{{uncategorized|date=May 2009}}