/* * Artificial Intelligence for Humans * Volume 2: Nature Inspired Algorithms * Java Version * http://www.aifh.org * http://www.jeffheaton.com * * Code repository: * https://github.com/jeffheaton/aifh * * Copyright 2014 by Jeff Heaton * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * * For more information on Heaton Research copyrights, licenses * and trademarks visit: * http://www.heatonresearch.com/copyright */ package com.heatonresearch.aifh.evolutionary.codec; import com.heatonresearch.aifh.evolutionary.genome.Genome; import com.heatonresearch.aifh.learning.MLMethod; /** * A CODEC defines how to transfer between a genome and phenome. Every CODEC * should support genome to phenome. However, not every code can transform a * phenome into a genome. */ public interface GeneticCODEC { /** * Decode the specified genome into a phenome. A phenome is an actual * instance of a genome that you can query. * * @param genome The genome to decode. * @return The phenome. */ MLMethod decode(Genome genome); /** * Attempt to build a genome from a phenome. Note: not all CODEC's support * this. If it is unsupported, an exception will be thrown. * * @param phenotype The phenotype. * @return The genome. */ Genome encode(MLMethod phenotype); }