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How to use heuristic method in fMBT

Best Python code snippet using fMBT_python

test_lm_cut.py

Source:test_lm_cut.py

...245            for f in heuristic.goal_plateau} == {heuristic.explicit_goal, 'g'}246def test_lm_cut_unsolvable():247    task = _get_simple_task_unsolvable()248    heuristic = LmCutHeuristic(task)249    h_val = heuristic(make_root_node(task.initial_state))250    heuristic.compute_goal_plateau(heuristic.explicit_goal)251    assert h_val == float('inf')252def test_lm_cut_at_goal():253    task = _get_simple_task_at_goal()254    heuristic = LmCutHeuristic(task)255    h_val = heuristic(make_root_node(task.initial_state))256    heuristic.compute_goal_plateau(heuristic.explicit_goal)257    assert h_val == 0.258def test_lm_cut_mark_multiple_goal():259    task = _get_intermediate_task()260    heuristic = LmCutHeuristic(task)261    heuristic.compute_hmax(task.initial_state)262    # artificially alter operator costs to get a larger goal plateau263    heuristic.relaxed_ops['op4'].cost = 0.264    heuristic.compute_goal_plateau(heuristic.explicit_goal)265    assert ({f.name for f in heuristic.goal_plateau} in266            [{heuristic.explicit_goal, 'v4', 'g'},267             {heuristic.explicit_goal, 'v5', 'g'}])268def test_two_times_hmax_same_result():269    task = _get_intermediate_task()270    heuristic = LmCutHeuristic(task)271    heuristic.compute_hmax(task.initial_state)272    heuristic.compute_hmax(task.initial_state)273    # artificially alter operator costs to get a larger goal plateau274    heuristic.relaxed_ops['op4'].cost = 0.275    heuristic.compute_goal_plateau(heuristic.explicit_goal)276    assert ({f.name for f in heuristic.goal_plateau} in277            [{heuristic.explicit_goal, 'v4', 'g'},278             {heuristic.explicit_goal, 'v5', 'g'}])279def test_lm_cut_compute_single_cut():280    task1 = _get_intermediate_task_two_paths()281    heuristic = LmCutHeuristic(task1)282    heuristic.compute_hmax(task1.initial_state)283    heuristic.goal_plateau.clear()284    heuristic.compute_goal_plateau(heuristic.explicit_goal)285    cut = heuristic.find_cut(task1.initial_state)286    assert [op.name for op in cut] == ['op4']287def test_lm_cut_heuristic_value():288    task1 = _get_intermediate_task_two_paths()289    heuristic = LmCutHeuristic(task1)290    h_val = heuristic(make_root_node(task1.initial_state))291    assert h_val == 4.292def test_lm_cut_heuristic_value_two_initial_facts():293    task1 = _get_intermediate_task_two_initial_facts()294    heuristic = LmCutHeuristic(task1)295    h_val = heuristic(make_root_node(task1.initial_state))296    assert h_val == 4.297def test_lm_cut_heuristic_value_simple_task_always_true():298    task1 = _get_simple_task_always_true()299    heuristic = LmCutHeuristic(task1)300    h_val = heuristic(make_root_node(task1.initial_state))301    #print('Printing goal plateau')302    #for f in heuristic.goal_plateau:303    #    print(repr(f))304    #print('Printing cut')305    #for op in cut:306    #    print(repr(op))307    assert h_val == 1.308def test_lm_cut_blocksworld_initial_state():309    parser = Parser('')310    parser.domInput = blocks_dom311    parser.probInput = blocks_problem_1312    domain = parser.parse_domain(False)313    problem = parser.parse_problem(domain, False)314    task = grounding.ground(problem)315    heuristic = LmCutHeuristic(task)316    h_val = heuristic(make_root_node(task.initial_state))317    assert h_val == 6.318def test_lm_cut_blocksworld_complete_astar():319    # run through plan and validate heuristic value320    # the true_h_values are taken from fast downward with astar and lm cut321    # heuristic322    true_h_values = [6., 5., 4., 3., 2., 1., 0.]323    plan_length = 6324    yield py.test.mark.slow(gen_blocks_test_astar), LmCutHeuristic, \325        true_h_values, plan_length326def test_lm_cut_blocksworld_complete_enforced_hillclimbing():327    true_h_values = [6.0, 5.0, 5.0, 4.0, 5.0, 5.0, 6.0, 5.0, 4.0, 3.0, 2.0,328                     1.0, 0.0]329    plan_length = 16330    # TODO: Result is currently undeterministic....

pyperplan.py

Source:pyperplan.py

1#! /usr/bin/env python32#3# This file is part of pyperplan.4#5# This program is free software: you can redistribute it and/or modify6# it under the terms of the GNU General Public License as published by7# the Free Software Foundation, either version 3 of the License, or8# (at your option) any later version.9#10# This program is distributed in the hope that it will be useful,11# but WITHOUT ANY WARRANTY; without even the implied warranty of12# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the13# GNU General Public License for more details.14#15# You should have received a copy of the GNU General Public License16# along with this program.  If not, see <http://www.gnu.org/licenses/>17#18# TODO: Give searches and heuristics commandline options and reenable preferred19# operators.20import sys21import os22import re23import logging24import subprocess25import time26try:27    import argparse28except ImportError:29    from external import argparse30from pddl.parser import Parser31import grounding32import search33import heuristics34import tools35from search.model_reconciliation import mce, mme36SEARCHES = {37    'astar': search.astar_search,38    'wastar': search.weighted_astar_search,39    'gbf': search.greedy_best_first_search,40    'bfs': search.breadth_first_search,41    'ehs': search.enforced_hillclimbing_search,42    'ids': search.iterative_deepening_search,43    'sat': search.sat_solve,44}45NUMBER = re.compile(r'\d+')46MRP = {47    'MME': mme.mme_search,48    'MCE': mce.mce_search49}50def get_heuristics():51    """52    Scan all python modules in the "heuristics" directory for classes ending53    with "Heuristic".54    """55    heuristics = []56    src_dir = os.path.dirname(os.path.abspath(__file__))57    heuristics_dir = os.path.abspath(os.path.join(src_dir, 'heuristics'))58    for filename in os.listdir(heuristics_dir):59        if not filename.endswith('.py'):60            continue61        module = tools.import_python_file(os.path.join(heuristics_dir, filename))62        heuristics.extend([getattr(module, cls) for cls in dir(module)63                           if cls.endswith('Heuristic') and cls != 'Heuristic' and64                           not cls.startswith('_')])65    return heuristics66def _get_heuristic_name(cls):67    name = cls.__name__68    assert name.endswith('Heuristic')69    return name[:-9].lower()70HEURISTICS = {_get_heuristic_name(heur): heur for heur in get_heuristics()}71def validator_available():72    return tools.command_available(['validate', '-h'])73def find_domain(problem):74    """75    This function tries to guess a domain file from a given problem file.76    It first uses a file called "domain.pddl" in the same directory as77    the problem file. If the problem file's name contains digits, the first78    group of digits is interpreted as a number and the directory is searched79    for a file that contains both, the word "domain" and the number.80    This is conforming to some domains where there is a special domain file81    for each problem, e.g. the airport domain.82    @param problem    The pathname to a problem file83    @return A valid name of a domain84    """85    dir, name = os.path.split(problem)86    number_match = NUMBER.search(name)87    number = number_match.group(0)88    domain = os.path.join(dir, 'domain.pddl')89    for file in os.listdir(dir):90        if 'domain' in file and number in file:91            domain = os.path.join(dir, file)92            break93    if not os.path.isfile(domain):94        logging.error('Domain file "{0}" can not be found'.format(domain))95        sys.exit(1)96    logging.info('Found domain {0}'.format(domain))97    return domain98def _parse(domain_file, problem_file):99    # Parsing100    parser = Parser(domain_file, problem_file)101    logging.info('Parsing Domain {0}'.format(domain_file))102    domain = parser.parse_domain()103    logging.info('Parsing Problem {0}'.format(problem_file))104    problem = parser.parse_problem(domain)105    logging.debug(domain)106    logging.info('{0} Predicates parsed'.format(len(domain.predicates)))107    logging.info('{0} Actions parsed'.format(len(domain.actions)))108    logging.info('{0} Objects parsed'.format(len(problem.objects)))109    logging.info('{0} Constants parsed'.format(len(domain.constants)))110    return problem111def _ground(problem):112    logging.info('Grounding start: {0}'.format(problem.name))113    task = grounding.ground(problem)114    logging.info('Grounding end: {0}'.format(problem.name))115    logging.info('{0} Variables created'.format(len(task.facts)))116    logging.info('{0} Operators created'.format(len(task.operators)))117    return task118def _search(task, search, heuristic, use_preferred_ops=False):119    logging.info('Search start: {0}'.format(task.name))120    if heuristic:121        if use_preferred_ops:122            solution = search(task, heuristic, use_preferred_ops)123        else:124            solution = search(task, heuristic)125    else:126        solution = search(task)127    logging.info('Search end: {0}'.format(task.name))128    return solution129def _write_solution(solution, filename):130    assert solution is not None131    with open(filename, 'w') as file:132        for op in solution:133            print(op.name, file=file)134def search_plan(domain_file, problem_file, search, heuristic_class,135                use_preferred_ops=False):136    """137    Parses the given input files to a specific planner task and then tries to138    find a solution using the specified  search algorithm and heuristics.139    @param domain_file      The path to a domain file140    @param problem_file     The path to a problem file in the domain given by141                            domain_file142    @param search           A callable that performs a search on the task's143                            search space144    @param heuristic_class  A class implementing the heuristic_base.Heuristic145                            interface146    @return A list of actions that solve the problem147    """148    problem = _parse(domain_file, problem_file)149    task = _ground(problem)150    heuristic = None151    if not heuristic_class is None:152        heuristic = heuristic_class(task)153    print(task)154    print(task.get_meta_task(task))155    search_start_time = time.clock()156    if use_preferred_ops and isinstance(heuristic, heuristics.hFFHeuristic):157        solution = _search(task, search, heuristic, use_preferred_ops=True)158    else:159        solution = _search(task, search, heuristic)160    logging.info('Wall-clock search time: {0:.2}'.format(time.clock() -161                                                         search_start_time))162    print(type(solution[0]))163    return solution164def search_explanation(domain1_file, problem1_file, domain2_file, problem2_file, search, heuristic_class, model_reconcilition):165    problem1 = _parse(domain1_file, problem1_file)166    robot_task = _ground(problem1)167    problem2 = _parse(domain2_file, problem2_file)168    human_task = _ground(problem2)169    heuristic = None170    if not heuristic_class is None:171        heuristic = heuristic_class(robot_task)172    if use_preferred_ops and isinstance(heuristic, heuristics.hFFHeuristic):173        p_r = _search(robot_task, search, heuristic, use_preferred_ops=True)174    else:175        p_r = _search(robot_task, search, heuristic)176    explanation = model_reconcilition(search, heuristic, p_r, robot_task, human_task)177    return explanation178def validate_solution(domain_file, problem_file, solution_file):179    if not validator_available():180        logging.info('validate could not be found on the PATH so the plan can '181                     'not be validated.')182        return183    cmd = ['validate', domain_file, problem_file, solution_file]184    exitcode = subprocess.call(cmd, stdout=subprocess.PIPE)185    if exitcode == 0:186        logging.info('Plan correct')187    else:188        logging.warning('Plan NOT correct')189    return exitcode == 0190if __name__ == '__main__':191    # Commandline parsing192    log_levels = ['debug', 'info', 'warning', 'error']193    # get pretty print names for the search algorithms:194    # use the function/class name and strip off '_search'195    def get_callable_names(callables, omit_string):196        names = [c.__name__ for c in callables]197        names = [n.replace(omit_string, '').replace('_', ' ') for n in names]198        return ', '.join(names)199    search_names = get_callable_names(SEARCHES.values(), '_search')200    argparser = argparse.ArgumentParser(201                        formatter_class=argparse.ArgumentDefaultsHelpFormatter)202    argparser.add_argument(dest='domain', nargs='?')203    argparser.add_argument(dest='problem')204    argparser.add_argument('-l', '--loglevel', choices=log_levels,205                           default='info')206    argparser.add_argument('-H', '--heuristic', choices=HEURISTICS.keys(),207                           help='Select a heuristic', default='hff')208    argparser.add_argument('-s', '--search', choices=SEARCHES.keys(),209        help='Select a search algorithm from {0}'.format(search_names),210        default='bfs')211    argparser.add_argument('-e', '--explanations', choices=["MME", "MCE"])212    argparser.add_argument('-d2', '--domain2')213    argparser.add_argument('-p2', '--problem2')214    args = argparser.parse_args()215    logging.basicConfig(level=getattr(logging, args.loglevel.upper()),216                    format='%(asctime)s %(levelname)-8s %(message)s',217                    stream=sys.stdout)218    hffpo_searches = ['gbf', 'wastar', 'ehs']219    if args.heuristic == 'hffpo' and args.search not in hffpo_searches:220        print('ERROR: hffpo can currently only be used with %s\n' %221              hffpo_searches, file=sys.stderr)222        argparser.print_help()223        exit(2)224    args.problem = os.path.abspath(args.problem)225    if args.domain is None:226        args.domain = find_domain(args.problem)227    else:228        args.domain = os.path.abspath(args.domain)229    search = SEARCHES[args.search]230    heuristic = HEURISTICS[args.heuristic]231    if args.search in ['bfs', 'ids', 'sat']:232        heuristic = None233    logging.info('using search: %s' % search.__name__)234    logging.info('using heuristic: %s' % (heuristic.__name__ if heuristic235                                          else None))236    use_preferred_ops = (args.heuristic == 'hffpo')237    if args.explanations is None:238        solution = search_plan(args.domain, args.problem, search, heuristic,239                               use_preferred_ops=use_preferred_ops)240        if solution is None:241            logging.warning('No solution could be found')242        else:243            solution_file = args.problem + '.soln'244            logging.info('Plan length: %s' % len(solution))245            _write_solution(solution, solution_file)246            validate_solution(args.domain, args.problem, solution_file)247    else:248        if args.domain2 is None or args.problem2 is None:249            print("Error: arguments 'domain2' and 'problem2' required when requesting explanations")250            exit(2)251        else:252            model_reconciliation = MRP[args.explanations]253            solution, explanation = search_explanation(args.domain, args.problem, args.domain2, args.problem2, search, heuristic, model_reconciliation)254            print("Solution :", solution)...

heuristic_test_instances.py

Source:heuristic_test_instances.py

...61"""62def _gen_h_values(initial_state, plan, heuristic):63    node = searchspace.SearchNode(initial_state, None, None, None)64    for op in plan:65        h_val = heuristic(node)66        yield h_val67        node = searchspace.SearchNode(op.apply(node.state), None, None, None)68    h_val = heuristic(node)69    yield h_val70def gen_heuristic_test(dom, prob, search_class, heuristic_class, h_values_plan,71                       plan_length=None):72    parser = Parser('')73    parser.domInput = dom74    parser.probInput = prob75    domain = parser.parse_domain(False)76    problem = parser.parse_problem(domain, False)77    task = grounding.ground(problem)78    heuristic = heuristic_class(task)79    plan = search_class(task, heuristic)80    if plan_length:81        assert len(plan) == plan_length82    # run through plan and validate heuristic value...

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