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Move utils in blackdrops
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‎include/blackdrops/reward/gp_reward.hpp‎

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#include <limbo/model/gp.hpp>
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#include <blackdrops/reward/reward.hpp>
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#include <utils/utils.hpp>
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#include <blackdrops/utils/utils.hpp>
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namespace blackdrops {
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‎include/blackdrops/system/dart_system.hpp‎

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#include <robot_dart/graphics/graphics.hpp>
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#endif
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#include <utils/utils.hpp>
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#include <blackdrops/utils/utils.hpp>
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namespace blackdrops {
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namespace system {

‎include/blackdrops/system/ode_system.hpp‎

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#define BLACKDROPS_SYSTEM_ODE_SYSTEM_HPP
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#include <boost/numeric/odeint.hpp>
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#include <utils/utils.hpp>
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#include <blackdrops/utils/utils.hpp>
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namespace blackdrops {
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namespace system {

‎include/blackdrops/utils/cmd_args.hpp‎

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//| Copyright Inria July 2017
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//| This project has received funding from the European Research Council (ERC) under
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//| the European Union's Horizon 2020 research and innovation programme (grant
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//| agreement No 637972) - see http://www.resibots.eu
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//|
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//| Contributor(s):
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//| - Konstantinos Chatzilygeroudis ([email protected])
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//| - Rituraj Kaushik ([email protected])
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//| - Roberto Rama ([email protected])
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//|
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//| This software is the implementation of the Black-DROPS algorithm, which is
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//| a model-based policy search algorithm with the following main properties:
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//| - uses Gaussian processes (GPs) to model the dynamics of the robot/system
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//| - takes into account the uncertainty of the dynamical model when
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//| searching for a policy
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//| - is data-efficient or sample-efficient; i.e., it requires very small
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//| interaction time with the system to find a working policy (e.g.,
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//| around 16-20 seconds to learn a policy for the cart-pole swing up task)
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//| - when several cores are available, it can be faster than analytical
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//| approaches (e.g., PILCO)
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//| - it imposes no constraints on the type of the reward function (it can
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//| also be learned from data)
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//| - it imposes no constraints on the type of the policy representation
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//| (any parameterized policy can be used --- e.g., dynamic movement
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//| primitives or neural networks)
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//|
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//| Main repository: http://github.com/resibots/blackdrops
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//| Preprint: https://arxiv.org/abs/1703.07261
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//|
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//| This software is governed by the CeCILL-C license under French law and
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//| abiding by the rules of distribution of free software. You can use,
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//| modify and/ or redistribute the software under the terms of the CeCILL-C
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//| license as circulated by CEA, CNRS and INRIA at the following URL
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//| "http://www.cecill.info".
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//|
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//| As a counterpart to the access to the source code and rights to copy,
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//| modify and redistribute granted by the license, users are provided only
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//| with a limited warranty and the software's author, the holder of the
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//| economic rights, and the successive licensors have only limited
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//| liability.
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//|
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//| In this respect, the user's attention is drawn to the risks associated
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//| with loading, using, modifying and/or developing or reproducing the
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//| software by the user in light of its specific status of free software,
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//| that may mean that it is complicated to manipulate, and that also
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//| therefore means that it is reserved for developers and experienced
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//| professionals having in-depth computer knowledge. Users are therefore
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//| encouraged to load and test the software's suitability as regards their
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//| requirements in conditions enabling the security of their systems and/or
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//| data to be ensured and, more generally, to use and operate it in the
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//| same conditions as regards security.
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//|
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//| The fact that you are presently reading this means that you have had
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//| knowledge of the CeCILL-C license and that you accept its terms.
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//|
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#ifndef BLACKDROPS_UTILS_CMD_ARGS_HPP
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#define BLACKDROPS_UTILS_CMD_ARGS_HPP
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#include <boost/program_options.hpp>
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namespace po = boost::program_options;
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namespace blackdrops {
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namespace utils {
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class CmdArgs {
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public:
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CmdArgs() : _verbose(false), _stochastic(false), _uncertainty(false), _threads(tbb::task_scheduler_init::automatic), _desc("Command line arguments") { _set_defaults(); }
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int parse(int argc, char** argv)
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{
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try {
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po::variables_map vm;
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po::store(po::parse_command_line(argc, argv, _desc), vm);
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if (vm.count("help")) {
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std::cout << _desc << std::endl;
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return 0;
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}
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po::notify(vm);
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if (vm.count("threads")) {
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_threads = vm["threads"].as<int>();
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}
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if (vm.count("hidden_neurons")) {
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int c = vm["hidden_neurons"].as<int>();
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if (c < 1)
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c = 1;
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_neurons = c;
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}
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else {
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_neurons = 5;
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}
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if (vm.count("pseudo_samples")) {
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int c = vm["pseudo_samples"].as<int>();
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if (c < 1)
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c = 1;
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_pseudo_samples = c;
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}
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else {
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_pseudo_samples = 10;
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}
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if (vm.count("boundary")) {
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double c = vm["boundary"].as<double>();
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if (c < 0)
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c = 0;
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_boundary = c;
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}
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else {
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_boundary = 0.;
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}
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// Cmaes parameters
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if (vm.count("max_evals")) {
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int c = vm["max_evals"].as<int>();
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_max_fun_evals = c;
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}
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else {
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_max_fun_evals = -1;
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}
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if (vm.count("tolerance")) {
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double c = vm["tolerance"].as<double>();
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if (c < 0.)
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c = 0.;
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_fun_tolerance = c;
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}
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else {
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_fun_tolerance = 1.;
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}
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if (vm.count("restarts")) {
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int c = vm["restarts"].as<int>();
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if (c < 1)
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c = 1;
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_restarts = c;
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}
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else {
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_restarts = 1;
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}
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if (vm.count("elitism")) {
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int c = vm["elitism"].as<int>();
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if (c < 0 || c > 3)
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c = 0;
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_elitism = c;
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}
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else {
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_elitism = 0;
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}
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if (vm.count("lambda")) {
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int l = vm["lambda"].as<int>();
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if (l < 0)
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l = -1;
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_lambda = l;
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}
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else {
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_lambda = -1;
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}
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}
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catch (po::error& e) {
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std::cerr << "[Exception caught while parsing command line arguments]: " << e.what() << std::endl;
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return 1;
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}
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return -1;
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}
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bool verbose() const { return _verbose; }
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bool stochastic() const { return _stochastic; }
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bool uncertainty() const { return _uncertainty; }
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int threads() const { return _threads; }
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int neurons() const { return _neurons; }
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int pseudo_samples() const { return _pseudo_samples; }
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int max_fun_evals() const { return _max_fun_evals; }
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int restarts() const { return _restarts; }
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int elitism() const { return _elitism; }
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int lambda() const { return _lambda; }
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double boundary() const { return _boundary; }
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double fun_tolerance() const { return _fun_tolerance; }
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protected:
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bool _verbose, _stochastic, _uncertainty;
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int _threads, _neurons, _pseudo_samples, _max_fun_evals, _restarts, _elitism, _lambda;
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double _boundary, _fun_tolerance;
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po::options_description _desc;
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void _set_defaults()
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{
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// clang-format off
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_desc.add_options()("help,h", "Prints this help message")
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("hidden_neurons,n", po::value<int>(), "Number of hidden neurons in NN policy.")
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("pseudo_samples,p", po::value<int>(), "Number of pseudo samples in GP policy.")
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("boundary,b", po::value<double>(), "Boundary of the values during the optimization.")
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("max_evals,m", po::value<int>(), "Max function evaluations to optimize the policy.")
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("tolerance,t", po::value<double>(), "Maximum tolerance to continue optimizing the function.")
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("restarts,r", po::value<int>(), "Max number of restarts to use during optimization.")
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("elitism,e", po::value<int>(), "Elitism mode to use [0 to 3].")
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("lambda,l", po::value<int>(), "Initial population of CMA-ES. Defaults to -1 (i.e., automatically determined).")
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("uncertainty,u", po::bool_switch(&_uncertainty)->default_value(false), "Enable uncertainty handling in CMA-ES.")
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("stochastic,s", po::bool_switch(&_stochastic)->default_value(false), "Enable stochastic rollouts (i.e., not use the mean model).")
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("threads,d", po::value<int>(), "Max number of threads used by TBB")
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("verbose,v", po::bool_switch(&_verbose)->default_value(false), "Enable verbose mode.");
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// clang-format on
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}
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};
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} // namespace utils
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} // namespace blackdrops
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#endif

‎include/utils/dart_utils.hpp‎ renamed to ‎include/blackdrops/utils/dart_utils.hpp‎

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#include <streambuf>
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#include <string>
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namespace utils {
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inline dart::dynamics::SkeletonPtr load_skel(const std::string& filename, const std::string& robot_name)
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{
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// Load file into string
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std::ifstream t(filename);
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std::string str((std::istreambuf_iterator<char>(t)),
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std::istreambuf_iterator<char>());
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namespace blackdrops {
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namespace utils {
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inline dart::dynamics::SkeletonPtr load_skel(const std::string& filename, const std::string& robot_name)
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{
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// Load file into string
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std::ifstream t(filename);
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std::string str((std::istreambuf_iterator<char>(t)),
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std::istreambuf_iterator<char>());
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dart::simulation::WorldPtr world = dart::utils::SkelParser::readWorldXML(str);
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dart::simulation::WorldPtr world = dart::utils::SkelParser::readWorldXML(str);
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return world->getSkeleton(robot_name);
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}
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}
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return world->getSkeleton(robot_name);
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}
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} // namespace utils
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} // namespace blackdrops
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#endif

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