legendtkl Requirements for Outputs
General Guidelines
PDDL Files
- Domain files must define actions with time constraints and resources.
- Problem files should specify deadlines for tasks.
- Schedules must follow sequential constraints.
Scheduler Behavior
- Scheduling must complete within a specified timeout.
- If no schedule exists, return an empty schedule or an explicit failure flag.
PDDL Scheduling Skills
1. Load Scheduling Domain and Problem
load-scheduling-problem(domain_path, problem_path)
Description:
Loads a PDDL domain file and problem file for scheduling tasks, creating a scheduling problem instance.
Parameters:
domain_path(str): Path to the PDDL domain file.problem_path(str): Path to the PDDL problem file.
Returns:
scheduling_problem: A scheduling problem object.
Example:
scheduling_problem = load_scheduling_problem("scheduling_domain.pddl", "tasks_to_schedule.pddl")
Notes:
- Uses
unified_planning.io.PDDLReader. - Raises an error if parsing fails.
2. Generate Schedule
generate-schedule(scheduling_problem)
Description: Generates a schedule for the specified planning problem based on task timings and deadlines.
Parameters:
scheduling_problem: A scheduling problem instance.
Returns:
schedule: A list of scheduled tasks with timing.
Example:
schedule = generate_schedule(scheduling_problem)
Notes:
- Uses
unified_planning.shortcuts.Scheduler. - Returns None if no schedule can be found.
3. Save Schedule
save-schedule(schedule, output_path)
Description: Writes the generated schedule to a file in a specified format suitable for scheduling applications.
Parameters:
schedule: A list of scheduled tasks.output_path(str): Path where the schedule will be saved.
Example:
save_schedule(schedule, "scheduled_tasks.txt")
Notes:
- Utilizes a specialized file writer for scheduling formats.
4. Validate Schedule
validate-schedule(scheduling_problem, schedule)
Description: Validates that the generated schedule meets the task requirements and deadlines specified in the problem.
Parameters:
scheduling_problem: The scheduling problem.schedule: The generated schedule.
Returns:
- bool: True if the schedule is valid, False otherwise.
Example:
is_valid = validate_schedule(scheduling_problem, schedule)
Notes:
- Uses
unified_planning.shortcuts.SchedulingValidator. - Ensures that task timing and resource allocation are correct.
Example Workflow
# Load scheduling problem
scheduling_problem = load_scheduling_problem("scheduling_domain.pddl", "tasks_to_schedule.pddl")
# Generate schedule
schedule = generate_schedule(scheduling_problem)
# Validate schedule
if not validate_schedule(scheduling_problem, schedule):
raise ValueError("Generated schedule is invalid")
# Save schedule
save_schedule(schedule, "scheduled_tasks.txt")
Notes
- This skill set aids in the effective scheduling of tasks within PDDL domains.
- Ideal for research in automated scheduling and resource management.