moses-ann-pole1.cc

/** moses-ann-pole1.cc ---
 *
 * Copyright (C) 2010-2011 OpenCog Foundation
 *
 * Author: Joel Lehman
 *
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU Affero General Public License v3 as
 * published by the Free Software Foundation and including the exceptions
 * at http://opencog.org/wiki/Licenses
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU Affero General Public License
 * along with this program; if not, write to:
 * Free Software Foundation, Inc.,
 * 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
 */
#include <iostream>
#include <opencog/util/mt19937ar.h>
#include <opencog/util/Logger.h>
#include <opencog/asmoses/combo/interpreter/eval.h>

#include <opencog/asmoses/moses/deme/deme_expander.h>
#include <opencog/asmoses/moses/metapopulation/metapopulation.h>
#include <opencog/asmoses/moses/moses/moses_main.h>
#include <opencog/asmoses/moses/representation/representation.h>
#include <opencog/asmoses/moses/optimization/optimization.h>
#include <opencog/asmoses/moses/scoring/scoring_base.h>

#include "pole_scoring.h"

using namespace std;
using namespace boost;
using namespace opencog;
using namespace moses;
using namespace reduct;

int main(int argc, char** argv)
{

    // Set flag to print only cassert and other ERROR level logs on stdout.
    logger().set_print_error_level_stdout();

    // Read in maximum evaluations and RNG seed from command line.
    int seed;
    bool reduce=true;
    try
    {
        if(argc < 6){
            cerr << "Not enough arguments." << endl;
            throw std::length_error("Missing arguments.");
        }
        // int max_evals=lexical_cast<int>(argv[1]);
        seed=lexical_cast<int>(argv[1]);

        set_stepsize(lexical_cast<double>(argv[2]));
        set_expansion(lexical_cast<double>(argv[3]));
        set_depth(lexical_cast<int>(argv[4]));

        reduce = lexical_cast<bool>(argv[5]);
    }
    catch (...)
    {
        cerr << "Usage: " << argv[0] << " seed step_size expansion depth reduce?{0,1}" << endl <<
            "ann_combo_tree" << endl <<
            "Example:" << endl <<
            "- Arguments: 1 1 2 5 1" << endl <<
            "- Ann Combo Tree: ann($N1($I2 $I3 $I4 $I5 $I6 0.0 0.0 0.0 0.0 0.0) $N7($I2 $I3 $I4 $I5 $I6 0.0 0.0 0.0 0.0 0.0))" << endl;
        exit(1);
    }

    // Read seed tree in from stdin.
    combo_tree tr;
    cin >> tr;

    randGen().seed(seed);

    type_tree tt(id::lambda_type);
    tt.append_children(tt.begin(), id::ann_type, 1);

    const reduct::rule* si = &(ann_reduction());
    if(!reduce)
        si = &(clean_reduction());

    //SINGLE MARKOVIAN POLE TASK
    ann_pole_bscore p_bscore;
    behave_cscore cscorer(p_bscore);

    univariate_optimization optim_algo;
    deme_expander dex(tt, *si,  *si, cscorer, optim_algo);
    metapopulation metapop_pole(tr, cscorer);

    moses_parameters pa;
    moses_statistics st;
    run_moses(metapop_pole, dex, pa, st);

    //change best tree into ANN
    tree_transform trans;
    combo_tree best = metapop_pole.best_tree();
    ann bestnet = trans.decodify_tree(best);

    //write out the best network
    cout << "Best network: " << endl;
    cout << &bestnet << endl;

    //write out in dot format
    bestnet.write_dot("best_nn.dot");

    //for parameter sweep
    cout << metapop_pole.best_score() << endl;
}