Planning to Learn Workshop (PlanLearn)


The task of constructing composite systems, that is systems composed of more than one part, can be seen as interdisciplinary area which builds on expertise in different domains. The aim of this workshop is to explore the possibilities of constructing such systems with the aid of Machine Learning and exploiting the know-how of Data Mining. One way of producing composite systems is by inducing the constituents and then by putting the individual parts together.
For instance, a text extraction system may be composed of various subsystems, some oriented towards tagging, morphosyntactic analysis or word sense disambiguation. This may be followed by selection of informative attributes and finally generation of the system for the extraction of the relevant information. Machine Learning techniques may be employed in various stages of this process.
The problem of constructing complex systems can thus be seen as a problem of planning to resolve multiple (possibly interacting) tasks. So, one important issue that needs to be addressed is how these multiple learning processes can be coordinated. Each task is resolved using certain ordering of operations. Meta-learning can be useful in this process. It can help us to retrieve previous solutions conceived in the past and re-use them in new settings.
The aim of the workshop is to explore the possibilities of this new area, offer a forum for exchanging ideas and experience concerning the state-of-the art, permit to bring in knowledge gathered in different but related and relevant areas and outline new directions for research.

Of particular interest are methods and proposals that address the following issues:

  • Planning to construct composite systems,
  • Exploitation of ontologies of tasks and methods,
  • Representation of learning goals and states in learning,
  • Control and coordination of learning processes,
  • Recovering / adapting sequences of DM operations,
  • Meta-learning and exploitation of meta-knowledge,
  • Layered learning,
  • Multi-task learning,
  • Transfer learning,
  • Multi-predicate learning (and other relevant ILP methods),
  • Combining induction and abduction,
  • Multi-strategy learning,
  • Learning to learn.

Other areas may be covered, provided they are relevant towards the overall aims of the workshop.


9:00 -10:30 Session 1

  • Ashwin Ram, Georgia Tech, USA (Invited speaker):
    New Directions in Goal-Driven Learning

  • Joaquin Vanschoren, Hendrik Blockeel, Bernhard Pfahringer and Geoffrey Holmes:
    Experiment Databases: Creating a New Platform for Meta-learning Research

10:30 - 11:00 Coffee break

11:00 -12:30 Session 2

  • Pedro Abreu, Carlos Soares and Jorge Valente:
    Learning to Plan: Selection of Heuristics for the Job-Shop Scheduling Problem based on the Prediction of Gaps in Machines

  • Alexandros Kalousis,  Abraham Bernstein, Melanie Hilario:
    Meta-learning with kernels and similarity functions for planning of data mining workflows

  • Monika Žáková, Petr Křemen, Filip Železný and Nada Lavrač:
    Planning to Learn with a Knowledge Discovery Ontology

  • Rui Leite and Pavel Brazdil:
    Selecting Classifiers Using Metalearning with Sampling Landmarks and Data Characterization

12:30 - 14:30 Lunch

14:45 -16:00 Session 3

  • José Ignacio Estévez, Pedro A. Toledo, José Sigut and Silvia Alayón:
    Learning to design complex systems using frequent graph patterns.

  • Raymond J. Mooney,  University of Texas at Austin  (Invited speaker):
    Transfer Learning by Mapping and Revising Relational Knowledge

16:00 - 16:30 Coffee break

16:30 - 18:00 Poster Session

The poster session will serve as a platform for discussion among participants. All presenters listed above are invited to prepare also a poster. In addition this session will include:

  • Filip Železný and Ondrej Kuželka:
    Learning to Plan and Planning to Learn via Merging Relational Machine Learning with Constraint Satisfaction


Important Dates

Submission deadline
(paper or extended abstract)

May 13, 2008 (extended fromMay 2, 2008)

Acceptance notification

May 26, 2008

Final Paper

June 20, 2008


July 9, 2008

Submission Instructions


  • The language of the workshop is English.
  • Papers should be in PDF format (and in exceptional circumstances in postscript); papers will not be accepted in any other format.
  • Papers should be at most 6 pages long.
  • All papers should be formatted in the style of ICML submission style (see templates at
    Note that exception that PlanLearn 2008 submissions are no double-blind!
  • All papers should include the names of the authors, their affiliations, their e-mail addresses, and an abstract on their first page.

Submission system:


Workshop organizers (Program Chair /Co-Chairs)

  • Pavel Brazdil, LIAAD-INESC L.A., University of Porto, pbrazdil AT
  • Abraham Bernstein, University of Zurich, Switzerland mail
  • Larry Hunter, Univ. of Colorado at Denver and Health Sciences Center, USA

Program Committee

  • Abraham Bernstein, University of Zurich, Switzerland
  • Pavel Brazdil, LIAAD, University of Porto, Portugal
  • Christophe Giraud-Carrier, Brigham Young University, USA
  • Saso Dzeroski, IJS, Ljubljana
  • Peter Flach, Univ. of Bristol, Great Britain
  • Larry Hunter, Univ. of Colorado at Denver and Health Sciences Center, USA
  • Rui Leite, LIAAD, University of Porto, Portugal
  • Tom Mitchell, Carnegie-Mellon Univ., USA (advisory role)
  • Oliver Ray, Univ. of Bristol, Great Britain
  • Ashwin Ram, Georgia Tech, USA
  • Luc de Raedt, University of Leuven, Belgium
  • Carlos Soares, LIAAD, University of Porto, Portugal
  • Maarten van Someren, University of Amsterdam, The Netherlands
  • Vojtech Svatek, Univ. of Economics, Prague, Czech Republic
  • Ricardo Vilalta, University of Houston, USA.
  • Filip Zelezny, Czech Technical University, Czech Republic

Previous workshops