248 lines
10 KiB
C++
248 lines
10 KiB
C++
#pragma once
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/*
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* Copyright (C) 2024 Brett Terpstra
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*
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* This program is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program. If not, see <https://www.gnu.org/licenses/>.
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*/
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#ifndef BLT_GP_SELECTION_H
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#define BLT_GP_SELECTION_H
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#include <blt/gp/fwdecl.h>
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#include <blt/gp/tree.h>
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#include <blt/gp/config.h>
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#include <blt/gp/random.h>
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#include <blt/std/assert.h>
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namespace blt::gp
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{
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struct selector_args
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{
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gp_program& program;
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population_t& next_pop;
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population_t& current_pop;
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population_stats& current_stats;
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prog_config_t& config;
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random_t& random;
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};
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constexpr inline auto perform_elitism = [](const selector_args& args) {
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auto& [program, next_pop, current_pop, current_stats, config, random] = args;
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if (config.elites > 0)
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{
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std::vector<std::pair<std::size_t, double>> values;
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for (blt::size_t i = 0; i < config.elites; i++)
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values.emplace_back(i, current_pop.get_individuals()[i].fitness.adjusted_fitness);
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for (const auto& ind : blt::enumerate(current_pop.get_individuals()))
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{
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for (blt::size_t i = 0; i < config.elites; i++)
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{
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//BLT_INFO("%lf >= %lf? // %lf", ind.second.fitness.adjusted_fitness, values[i].second, ind.second.fitness.raw_fitness);
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if (ind.second.fitness.adjusted_fitness >= values[i].second)
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{
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bool doesnt_contain = true;
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for (blt::size_t j = 0; j < config.elites; j++)
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{
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if (ind.first == values[j].first)
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doesnt_contain = false;
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}
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if (doesnt_contain)
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values[i] = {ind.first, ind.second.fitness.adjusted_fitness};
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break;
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}
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}
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}
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for (blt::size_t i = 0; i < config.elites; i++)
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next_pop.get_individuals().push_back(current_pop.get_individuals()[values[i].first]);
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}
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};
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template<typename Crossover, typename Mutation, typename Reproduction>
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constexpr inline auto proportionate_next_pop_creator = [](
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const selector_args& args, Crossover crossover_selection, Mutation mutation_selection, Reproduction reproduction_selection) {
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auto& [program, next_pop, current_pop, current_stats, config, random] = args;
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double total_prob = config.mutation_chance + config.crossover_chance;
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double crossover_chance = config.crossover_chance / total_prob;
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double mutation_chance = crossover_chance + config.mutation_chance / total_prob;
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perform_elitism(args);
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while (next_pop.get_individuals().size() < config.population_size)
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{
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auto type = random.get_double();
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if (type > crossover_chance && type < mutation_chance)
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{
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// crossover
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auto& p1 = crossover_selection.select(program, current_pop, current_stats);
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auto& p2 = crossover_selection.select(program, current_pop, current_stats);
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auto results = config.crossover.get().apply(program, p1, p2);
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// if crossover fails, we can check for mutation on these guys. otherwise straight copy them into the next pop
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if (results)
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{
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next_pop.get_individuals().emplace_back(std::move(results->child1));
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// annoying check
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if (next_pop.get_individuals().size() < config.population_size)
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next_pop.get_individuals().emplace_back(std::move(results->child2));
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} else
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{
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if (config.try_mutation_on_crossover_failure && random.choice(config.mutation_chance))
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next_pop.get_individuals().emplace_back(std::move(config.mutator.get().apply(program, p1)));
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else
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next_pop.get_individuals().push_back(individual{p1});
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// annoying check.
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if (next_pop.get_individuals().size() < config.population_size)
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{
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if (config.try_mutation_on_crossover_failure && random.choice(config.mutation_chance))
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next_pop.get_individuals().emplace_back(std::move(config.mutator.get().apply(program, p2)));
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else
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next_pop.get_individuals().push_back(individual{p2});
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}
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}
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} else if (type > mutation_chance)
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{
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// mutation
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auto& p = mutation_selection.select(program, current_pop, current_stats);
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next_pop.get_individuals().emplace_back(std::move(config.mutator.get().apply(program, p)));
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} else
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{
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// reproduction
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auto& p = reproduction_selection.select(program, current_pop, current_stats);
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next_pop.get_individuals().push_back(individual{p});
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}
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}
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};
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template<typename Crossover, typename Mutation, typename Reproduction>
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constexpr inline auto default_next_pop_creator = [](
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const blt::gp::selector_args& args, Crossover crossover_selection, Mutation mutation_selection, Reproduction reproduction_selection) {
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auto& [program, next_pop, current_pop, current_stats, config, random] = args;
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perform_elitism(args);
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while (next_pop.get_individuals().size() < config.population_size)
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{
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int sel = random.get_i32(0, 3);
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switch (sel){
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case 0:
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// everyone gets a chance once per loop.
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if (random.choice(config.crossover_chance))
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{
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// crossover
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auto& p1 = crossover_selection.select(program, current_pop, current_stats);
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auto& p2 = crossover_selection.select(program, current_pop, current_stats);
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auto results = config.crossover.get().apply(program, p1, p2);
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// if crossover fails, we can check for mutation on these guys. otherwise straight copy them into the next pop
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if (results)
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{
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next_pop.get_individuals().emplace_back(std::move(results->child1));
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// annoying check
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if (next_pop.get_individuals().size() < config.population_size)
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next_pop.get_individuals().emplace_back(std::move(results->child2));
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}
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}
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break;
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case 1:
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if (random.choice(config.mutation_chance))
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{
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// mutation
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auto& p = mutation_selection.select(program, current_pop, current_stats);
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next_pop.get_individuals().emplace_back(std::move(config.mutator.get().apply(program, p)));
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}
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break;
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case 2:
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if (config.reproduction_chance > 0 && random.choice(config.reproduction_chance))
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{
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// reproduction
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auto& p = reproduction_selection.select(program, current_pop, current_stats);
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next_pop.get_individuals().push_back(individual{p});
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}
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break;
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default:
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BLT_ABORT("This is not possible!");
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}
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}
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};
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class selection_t
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{
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public:
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/**
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* @param program gp program to select with, used in randoms
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* @param pop population to select from
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* @param stats the populations statistics
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* @return
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*/
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virtual tree_t& select(gp_program& program, population_t& pop, population_stats& stats) = 0;
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virtual void pre_process(gp_program&, population_t&, population_stats&)
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{}
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virtual ~selection_t() = default;
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};
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class select_best_t : public selection_t
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{
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public:
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tree_t& select(gp_program& program, population_t& pop, population_stats& stats) final;
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};
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class select_worst_t : public selection_t
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{
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public:
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tree_t& select(gp_program& program, population_t& pop, population_stats& stats) final;
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};
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class select_random_t : public selection_t
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{
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public:
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tree_t& select(gp_program& program, population_t& pop, population_stats& stats) final;
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};
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class select_tournament_t : public selection_t
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{
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public:
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explicit select_tournament_t(blt::size_t selection_size = 3): selection_size(selection_size)
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{
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if (selection_size < 1)
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BLT_ABORT("Unable to select with this size. Must select at least 1 individual!");
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}
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tree_t& select(gp_program& program, population_t& pop, population_stats& stats) final;
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private:
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const blt::size_t selection_size;
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};
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class select_fitness_proportionate_t : public selection_t
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{
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public:
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void pre_process(gp_program& program, population_t& pop, population_stats& stats) final;
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tree_t& select(gp_program& program, population_t& pop, population_stats& stats) final;
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};
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}
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#endif //BLT_GP_SELECTION_H
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