Exemplo n.º 1
0
def reschedule_stream_plan(evaluations,
                           target_facts,
                           domain,
                           stream_results,
                           unique_binding=False,
                           unsatisfiable=False,
                           max_effort=INF,
                           planner=RESCHEDULE_PLANNER,
                           debug=False):
    # TODO: search in space of partially ordered plans
    # TODO: constrain selection order to be alphabetical?
    domain.actions[:], stream_result_from_name = get_stream_actions(
        stream_results, unique_binding=unique_binding)
    goal_expression = And(*target_facts)
    if unsatisfiable:  # TODO: ensure that the copy hasn't harmed anything
        goal_expression = add_unsatisfiable_to_goal(domain, goal_expression)
    reschedule_problem = get_problem(evaluations,
                                     goal_expression,
                                     domain,
                                     unit_costs=False)
    reschedule_task = task_from_domain_problem(domain, reschedule_problem)
    #reschedule_task.axioms = [] # TODO: ensure that the constants are added in the event that axioms are needed?
    sas_task = sas_from_pddl(reschedule_task)
    stream_names, effort = solve_from_task(sas_task,
                                           planner=planner,
                                           max_planner_time=10,
                                           max_cost=max_effort,
                                           debug=debug)
    if stream_names is None:
        return None
    stream_plan = [stream_result_from_name[name] for name, _ in stream_names]
    return stream_plan
Exemplo n.º 2
0
def solve_sequential(evaluations,
                     goal_exp,
                     domain,
                     unit_costs=False,
                     debug=False,
                     **search_args):
    problem = get_problem(evaluations, goal_exp, domain, unit_costs)
    task = task_from_domain_problem(domain, problem)
    if has_attachments(domain):
        with Verbose(debug):
            instantiated = instantiate_task(task)
        return solve_pyplanners(instantiated, **search_args)
    sas_task = sas_from_pddl(task, debug=debug)
    return abstrips_solve_from_task(sas_task, debug=debug, **search_args)
Exemplo n.º 3
0
def solve_finite(evaluations, goal_exp, domain, unit_costs=False, debug=False, **search_args):
    if isinstance(domain, SimplifiedDomain):
        problem = get_problem_pddl(evaluations, goal_exp, domain.pddl)
        pddl_plan, cost = solve_tfd(domain.pddl, problem, debug=debug)
    else:
        problem = get_problem(evaluations, goal_exp, domain, unit_costs)
        task = task_from_domain_problem(domain, problem)
        if has_attachments(domain):
            with Verbose(debug):
                instantiated = instantiate_task(task)
            pddl_plan, cost = solve_pyplanners(instantiated, **search_args)
        else:
            sas_task = sas_from_pddl(task, debug=debug)
            pddl_plan, cost = abstrips_solve_from_task(sas_task, debug=debug, **search_args)
    plan = obj_from_pddl_plan(pddl_plan)
    return plan, cost
Exemplo n.º 4
0
def solve_finite(evaluations,
                 goal_exp,
                 domain,
                 unit_costs=False,
                 debug=False,
                 **search_args):
    if isinstance(domain, SimplifiedDomain):
        problem = get_problem_pddl(evaluations, goal_exp, domain.pddl)
        pddl_plan, cost = solve_tfd(domain.pddl, problem, debug=debug)
    else:
        task = task_from_domain_problem(
            domain, get_problem(evaluations, goal_exp, domain, unit_costs))
        sas_task = sas_from_pddl(task, debug=debug)
        pddl_plan, cost = abstrips_solve_from_task(sas_task,
                                                   debug=debug,
                                                   **search_args)
    plan = obj_from_pddl_plan(pddl_plan)
    return plan, cost