Genetic Programming Bibliography entries for Peter Ross
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GP coauthors/coeditors:
Chris Gathercole,
Genetic Programming conference papers by Peter Ross
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Chris Gathercole and Peter Ross.
Small Populations over Many Generations can beat Large Populations over Few Generations in Genetic Programming. In
John R. Koza and Kalyanmoy Deb and Marco Dorigo and David B. Fogel and Max Garzon and Hitoshi Iba and Rick L. Riolo editors,
Genetic Programming 1997: Proceedings of the Second Annual Conference, pages 111-118, Stanford University, CA, USA, 1997. Morgan Kaufmann.
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Chris Gathercole and Peter Ross.
Tackling the Boolean Even N Parity Problem with Genetic Programming and Limited-Error Fitness. In
John R. Koza and Kalyanmoy Deb and Marco Dorigo and David B. Fogel and Max Garzon and Hitoshi Iba and Rick L. Riolo editors,
Genetic Programming 1997: Proceedings of the Second Annual Conference, pages 119-127, Stanford University, CA, USA, 1997. Morgan Kaufmann.
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Chris Gathercole and Peter Ross.
An Adverse Interaction between Crossover and Restricted Tree Depth in Genetic Programming. In
John R. Koza and David E. Goldberg and David B. Fogel and Rick L. Riolo editors,
Genetic Programming 1996: Proceedings of the First Annual Conference, pages 291-296, Stanford University, CA, USA, 1996. MIT Press.
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Chris Gathercole and Peter Ross.
Dynamic Training Subset Selection for Supervised Learning in Genetic Programming. In
Yuval Davidor and Hans-Paul Schwefel and Reinhard M\"anner editors,
Parallel Problem Solving from Nature III, volume 866, pages 312-321, Jerusalem, 1994. Springer-Verlag.
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Genetic Programming technical reports by Peter Ross
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Chris Gathercole and Peter Ross.
The MAX Problem for Genetic Programming - Highlighting an Adverse Interaction between the Crossover Operator and a Restriction on Tree Depth. Technical report,
Department of Artificial Intelligence, University of Edinburgh, 80 South Bridge, Edinburgh, EH1 1HN, UK , 1995.
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Genetic Programming etc Peter Ross
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Chris Gathercole and Peter Ross.
Some Training Subset Selection Methods for Supervised Learning in Genetic Programming.
Presented at ECAI'94 Workshop on Applied Genetic and other Evolutionary Algorithms. 1994.
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