Homepage PbP

Welcome to the homepage of

A Portfolio-based Planner

Winner of the learning track of the 6th International Planning Competition (IPC6)
Winner of the learning track of the 7th International Planning Competition (IPC7)

The PbP Approach version 2.0 (June 2012)

PbP is an automated system that generates efficient domain-specific multi-planners from a portfolio of domain-independent planning techniques by (i) computing some sets of macro-actions for every planner in the portfolio, (ii) optimizing the parameter setting of the parameterized planners in the portfolio, (iii) selecting a promising combination of planners in the portfolio and relative useful macro-actions, and (iv) defining some running time slots for their round-robin scheduling during planning. The configuration of the portfolio yielding the multi-planner relies on some knowledge about the performance of the planners and relative macro-actions, which is automatically generated from a training problem set.

We developed two versions of PbP:

PbP.s finds as quickly as possible a plan and then stops;
PbP.q finds a good quality plan using all the given CPU-time.

Download of PbP.s (executable code)
Download of PbP.q (executable code)

Main papers related to PbP

Alfonso Gerevini, Alessandro Saetti, Mauro Vallati, An Automatically Configurable Portfolio-based Planner with Macro-actions: PbP, Proceedings of the 19th International Conference on Automated Planning & Scheduling ( ICAPS-09 ), 19-23, AAAI, Thessaloniki (Greece), 2009.

Alfonso Gerevini, Alessandro Saetti, Mauro Vallati, Learning and Exploiting Configuration Knowledge for a Portfolio-based Planner, Working notes of 19th International Conference on Automated Planning & Scheduling ( ICAPS-09 ) - Workshop on Planning and Learning, Thessaloniki (Greece), 2009.

PbP Team

Current members: Alfonso E. Gerevini , Alessandro Saetti, Mauro Vallati
Planning group coordinator: Alfonso E. Gerevini
Undergraduate students (now graduated) previously involved: Beniamino Galvani.

June 21, 2012