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This is the website for the learning tracks of the IPC 2023.

Below is our preliminary plan. Details might change and feedback is welcome!

Setup

The learning tracks use a similar setup as in 2008, 2011 and 2014. The main difference is that participants don’t have access to the selected PDDL domains and they don’t learn the domain knowledge themselves. Instead, they submit a fully automated learning system. Then the organizers learn the domain knowledge and evaluate the submitted planners on unseen test instances from the same domain. The main motivation for this setup is to make it easier to run learning systems from other authors, which increases reproducibility and helps to turn learning algorithms into off-the-shelve tools.

Participants will submit two Singularity scripts:

We call a domain polynomial if all its tasks can be solved suboptimally in polynomial time. The competition will include both polynomial and non-polynomial domains.

Example domain knowledge includes but is not limited to:

For example PDDL tasks, see https://github.com/aibasel/downward-benchmarks.

Calls

Comming soon

Preliminary Schedule

Event Date
Call for domains / expression of interest July, 2022
Domain submission deadline December, 2022
Demo problems provided December, 2022
Initial planner submission January, 2023
Feature stop (final planner submission) March, 2023
Planner Abstract submission deadline May, 2023
Contest run May - June, 2023
Results announced July, 2023
Result analysis deadline August, 2023

Tracks

Single-Core Track

Multi-Core Track

Metrics

If an invalid plan is returned (or suboptimal plan for optimal metric), all tasks in the domain are counted as unsolved. If that happens in more than one domain, the entry is disqualified.

Optimal

Satisficing

Agile

PDDL Fragment

Learners and planners must support the following subset of PDDL 3.1: STRIPS, action costs, types, negative preconditions.

Registration

Coming soon

Organizers

Contact: jendrik.seipp@liu.se,javier/dot/segovia/at/upf/dot/edu