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Last change
on this file since 1148 was
1147,
checked in by Maciej Komosinski, 4 years ago
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Multi-criteria optimization, can optionally include diversity is one criterion
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File size:
844 bytes
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| [1113] | 1 | rem To learn about all available options of each .py algorithm, add "-h" to its parameters.
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| 2 | rem Use the source code of the examples as a starting point for your customizations.
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| 3 | rem Example usage:
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| 4 |
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| [1117] | 5 | set DIR_WITH_FRAMS_LIBRARY=............
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| [1113] | 6 |
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| 7 |
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| [1117] | 8 | python -m evolalg.examples.standard -path %DIR_WITH_FRAMS_LIBRARY% -opt numneurons
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| [1113] | 9 |
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| [1145] | 10 | python -m evolalg.examples.niching_novelty -path %DIR_WITH_FRAMS_LIBRARY% -opt velocity -max_numparts 6 -debug
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| 11 |
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| 12 | python -m evolalg.examples.niching_novelty -path %DIR_WITH_FRAMS_LIBRARY% -opt vertpos -fit knn_niching -knn 3 -max_numjoints 8 -popsize 10 -generations 30
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| [1147] | 13 |
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| 14 | rem '-dissim ...' can be used to include dissimilarity as one of the criteria
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| 15 | python -m evolalg.examples.multicriteria -path %DIR_WITH_FRAMS_LIBRARY% -popsize 40 -generations 10 -opt velocity,vertpos
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