Welcome to the
is an innovative case-based planning system which is able to
efficiently retrieve planning cases from plan libraries with more than
ten thousands elements, heuristically choose a suitable candidate
(possibly the best one) and adapt it to provide a good quality solution
plan similar to the one retrieved from the case base.
Given a planning problem we encode it as a compact graph structure,
that we call Planning Encoding Graph,
description of the topology
of the planning problem.
By using this graph representation, we examine an approximate retrieval
procedure based on kernel functions
that leads to effectively face the problem of matching planning
instances, allowing to achieve extremely good performance in standard
Overall, we show that OAKplan is competitive with state of the art plan
generation systems in terms of number of problems solved, CPU time,
plan difference values and plan quality when cases similar to the current planning
problem are available into the plan library.
Download of OAKplan 1.0 (executable code)
Download of OAKplan 2.0 (executable code also for metric-temporal domains)
Download of case and test problems (Metric and Temporal-Metric domains)
Main papers related to OAKplan
- A. Bonisoli, A. Gerevini, A. Saetti, I. Serina. "Effective plan retrieval in case-based planning for metric-temporal problems".
Journal of Experimental & Theoretical Artificial Intelligence.
Volume 27, Issue 5, 2015. Special Issue: Knowledge
Representation and Automated Reasoning. Pages 603-647. DOI:
10.1080/0952813X.2014.993506. (PDF file)
- D. Borrajo, A. Roubickova, I. Serina. 2015. "Progress in Case-Based Planning". ACM Computing Survey. 47, 2, Article 35 (January 2015), 39 pages. DOI=10.1145/2674024 (PDF file)
- M.Vallati, I. Serina, A. Saetti, A. Gerevini. "Identifying and Exploiting Features for Effective Plan Retrieval in Case-Based Planning".
Proceedings of the International Conference on Automated
Planning & Scheduling (ICAPS15). Jerusalem (Israel). June 2015.(PDF file)
Alfonso Gerevini, Anna Roubickova, Alessandro Saetti, Ivan Serina, "Offline and Online Plan Library Maintenance in Case-based Planning",
Proceedings of the Thirteenth Conferen- ce of the Italian Association for Artificial Intelligence (AIIA-13), Turin (Italy), 2013.
Alfonso Gerevini, Anna Roubickova, Alessandro Saetti, Ivan Serina,
"On the Plan-library Maintenance Problem in a Case-based Planner",
Proceedings of the 21st International Conference on Case-Based Reasoning (ICCBR-13), Saratoga Springs (NY), 2013.
Alfonso Gerevini, Alessandro Saetti, Ivan Serina, "Case-based Planning for Problems with Real-valued Fluents: Kernel Functions
for Effective Plan Retrieval",
Proceedings of the 20th European Conference on Artificial
Intelligence (ECAI-12), Montpellier (France), 2012.
file) (bib entry)
- A. Garrido, L. Morales, I. Serina."Using AI Planning to Enhance E-learning Processes".
Proceedings of the Twenty-Second International Conference on Automated
Planning and Scheduling (ICAPS-2012), AAAI Press, pp. 47-55, 2012. (PDF file)
- L. Morales, A. Garrido, I. Serina. "Planning and Execution in a Personalized E-learning Setting".
Proceedings of the Conferencia de la Asociación Española para la
Inteligencia Artificial (CAEPIA-2011). San Cristóbal de La Laguna,
Tenerife. 7-10 Novembre 2011. (PDF file)
Ivan Serina, "Kernel Functions for Case-Based Planning". Artificial
Intelligence, vol 174: 1369 – 1406, 2010. Also
published online by Elsevied
ScienceDirect at the following. (DOI link) (PDF file)
Ivan Serina, "Kernel Functions for
Case-Based Planning". Technical
ieport - Free University of Bozen. May 2010.