rem To learn about all available options of each .py algorithm below, add "-h" to its parameters. rem Use the source code of the examples as a starting point for your customizations. rem Example usage: set DIR_WITH_FRAMS_LIBRARY=............ rem simple one-criterion evolution from minimalistic example source (examples.standard) python -m evolalg_steps.examples.standard -path %DIR_WITH_FRAMS_LIBRARY% -opt numneurons rem as above but "chaining" .sim files, subsequent files overwrite selected parameters python -m evolalg_steps.examples.standard -path %DIR_WITH_FRAMS_LIBRARY% -sim eval-allcriteria.sim;deterministic.sim;sample-period-longest.sim -opt velocity rem simple one-criterion evolution but more options available in examples.niching_novelty, here: hard limit on the number of Parts and debugging messages python -m evolalg_steps.examples.niching_novelty -path %DIR_WITH_FRAMS_LIBRARY% -opt velocity -max_numparts 6 -debug rem "local" niching python -m evolalg_steps.examples.niching_novelty -path %DIR_WITH_FRAMS_LIBRARY% -opt vertpos -fit knn_niching -knn 3 -max_numjoints 8 -popsize 10 -generations 30 rem two criteria, '-dissim ...' can also be used to include dissimilarity as one of the criteria python -m evolalg_steps.examples.multicriteria -path %DIR_WITH_FRAMS_LIBRARY% -popsize 40 -generations 10 -opt velocity,vertpos