Scientific Publications of Kurt Driessens

 

Articles in international reviewed journals


  1. 1.K. Driessens, J. Ramon and T. Gaertner, Gaussian Processes as Regression technique for Relational Reinforcement Learning, Machine Learning 64, pp. 91-119, 2006

  2. 2.K. Driessens, Relational reinforcement learning, AI Communications 18, pp 71-73, 2005

  3. 3.K. Driessens, and S. Dzeroski, Integrating guidance into relational reinforcement learning, Mach. Learn. 57, pp. 271-304, 2004

  4. 4.S. Dzeroski, L. De Raedt, and K. Driessens, Relational reinforcement learning, Mach. Learn. 43, pp. 7-52, 2001


Contributions at international conferences, published in proceedings

Conference Proceedings with International Publisher

  1. 5.S. Sanner, R. Goetschalckx, K. Driessens and G. Shani, Bayesian Real-time Dynamic Programming, Proceedings of the 21st International Joint Conference on Artificial Intelligence, IJCAI-09, Pasadena, USA, pp. 1784-1789, 2009

  2. 6.G. Van den Broeck, K. Driessens, J. Ramon, Monte-Carlo tree search in poker using expected reward distributions, Proceedings of the first Asian Conference on Machine Learning, ACML 2009, Nanjing, China, Lecture Notes in Computer Science, LNCS 5828, pp. 367-381, Springer, 2009

  3. 7.M. Ponsen, T. Croonenborghs, K. Tuyls, J. Ramon and K. Driessens, Learning with whom to communicate using relational reinforcement learning, Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2009, Budapest, Hungary, (Sierra, C., Castelfranchi, C., Decker, K., Sichman, J., Eds.) pp. 1221-1222, 2009

  4. 8.R. Goetschalckx, S. Sanner and K. Driessens, Cost-Sensitive Parsimonious Linear Regression, Proceedings of the 8th IEEE International Conference on Data Mining, ICDM 2008, Pisa, Italy, pp. 809-814, IEEE Computer Society, 2008

  5. 9.K. Kersting and K. Driessens, Non-Parametric Policy Gradients, Proceedings of the 25th International Conference on Machine Learning, ICML 2008, Helsinki, Finland (A. McCallum and S. Roweis, Eds.), pp. 456-463, 2008

  6. 10.R. Goetschalckx, S. Sanner and K. Driessens, Reinforcement Learning with the Use of Costly Features, Proceedings of the European Workshop on Reinforcement Learning, EWRL 2008, Villeneuve d’Ascq, France, Lecture Notes in Computer Science, LNCS, 5323, art.nr. 10, 2008

  7. 11.M. Ponsen, K. Tuyls, T. Croonenborghs, J. Ramon and K. Driessens, Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker, Proceedings of the 23rd AAAI Conference on Artificial Intelligence, AAAI 2008, Chicago, USA (D. Fox and C.P. Gomes, Eds.), pp. 1485-1486, 2008

  8. 12.L. Antanas, K. Driessens, J. Ramon and Tom Croonenborghs, Using Decision Trees as the Answer Networks in Temporal Difference-Networks, Proceedings of the 18th European Conference on Artificial Intelligence, ECAI 2008, Patras, Greece (M. Ghallab et al. Eds.), pp. 847-848, 2008

  9. 13.R. Goetschalckx, S. Sanner and K. Driessens, Reinforcement Learning with the Use of Costly Features, Proceedings of the 18th European Conference on Artificial Intelligence, ECAI 2008, Patras, Greece (M. Ghallab et al. Eds.), pp. 779-780, 2008

  10. 14.T. Croonenborghs, K. Driessens and M. Bruynooghe, Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning, Proceedings of the 17th Annual International Conference on Inductive Logic Programming, ILP 2007, Corvallis, Oregon, USA, (Blockeel, et al. Eds.) vol 4894, Lecture Notes in Computer Science, pp. 88-97, 2008

  11. 15.J. Ramon, K. Driessens and T. Croonenborghs, Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling, Proceedings of the 18th European Conference on Machine Learning, ECML 2007, Warsaw, Poland (Kok, J. et al. Eds.), vol 4701, Lecture Notes in Artificial Intelligence, pp. 699-707, 2007

  12. 16.K. Driessens, P. Reutemann, B. Pfahringer and C. Leschi, Using Weighted Nearest Neighbor to Benefit from Unlabeled Data, Proceedings of the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006), Singapore, (Wee Keong Ng et al., eds.), vol 3918, Lecture Notes in Computer Science, pp. 60-69, 2006.

  13. 17.K. Driessens and S. Dzeroski, Combining Model-Based and Instance-Based Learning for First Order Regression, Proceedings of the 22nd International Conference on Machine Learning, ICML 2005 (De Raedt, L. and Wrobel, S., eds.), pp. 193-200, 2005

  14. 18.T. Gartner, K. Driessens, and J. Ramon, Graph kernels and Gaussian processes for relational reinforcement learning, Proceedings of the 13th International Conference on Inductive Logic Programming, ILP 2003 (Horvath, T. and Yamamoto, A., eds.), vol 2835, Lecture Notes in Computer Science, pp. 146-163, 2003

  15. 19.K. Driessens, and J. Ramon, Relational instance based regression for relational reinforcement learning, Proceedings of the Twentieth International Conference on Machine Learning (Fawcett, T. and Mishra, N., eds.), pp. 123-130, 2003

  16. 20.K. Driessens, and S. Dzeroski, Integrating experimentation and guidance in relational reinforcement learning, Proceedings of the Nineteenth International Conference on Machine Learning (Sammut, C. and Hoffmann, A., eds.), pp. 115-122, 2002

  17. 21.K. Driessens, J. Ramon, and H. Blockeel, Speeding up relational reinforcement learning through the use of an incremental first order decision tree algorithm, Proceedings of ECML - European Conference on Machine Learning (De Raedt, Luc and Flach, Peter, eds.), vol 2167, LNAI, pp. 97-108, 2001

  18. 22.N. Jacobs, K. Driessens, and L. De Raedt, Using ILP systems for verification and validation of multi agent systems, Proceedings of 8th International Conference on Inductive Logic Programming (ILP'98), Madison, Wisconsin, USA (Page, D., ed.), vol 1446, Lecture Notes in Artificial Intelligence, pp. 145-154, 1998

  19. 23.K. Driessens, N. Jacobs, N. Cossement, P. Monsieurs, and L. De Raedt, Inductive verification and validation of the KULRot RoboCup team, Proceedings of the Second RoboCup Workshop (Asada, M., ed.), vol 1604, Lecture Notes in Computer Science, pp.193-206, 1998

Other

  1. 24.W. Labeeuw, K. Driessens, D. Weyns, T. Holvoet, G. Deconinck, Prediction of Congested Traffic on the Critical Density Point Using Machine Learning and Decentralised Collaborating Cameras, New Trends in Artificial Intelligence, 14th Portuguese Conference on Artificial Intelligence, EPIA 2009, Aveiro, Portugal, pp. 15-26, 2009

  2. 25.G. Van den Broeck, K. Driessens, J. Ramon, Monte-Carlo tree search in poker using expected reward distributions, Proceedings of the 21st Benelux Conference on Artificial Intelligence, BNAIC 2009, Eindhoven, The Netherlands, 2009

  3. 26.M. Ponsen, K. Tuyls, S. de Jong, J. Ramon, T. Croonenborghs and K. Driessens, The Dynamics of Human Behaviour in Poker, Proceedings of the 20th Belgian-Netherlands Conference on Artificial Intelligence, BNAIC 2008, Twente, The Netherlands, accepted, 2008

  4. 27.T. Croonenborghs, K. Driessens and M. Bruynooghe, Learning a Transfer Function for Reinforcement Learning Problems, Proceedings of the Annual Belgian-Dutch Machine Learning Conference, Benelearn 2008, Spa, Belgium, (Wehenkel et al., Eds.), pp. 15-16, 2008

  5. 28.R. Goetschalckx, S. Sanner and K. Driessens, Linear Regression using Costly Features, Proceedings of the Annual Belgian-Dutch Machine Learning Conference, Benelearn 2008, Spa, Belgium, (Wehenkel et al., Eds.), pp. 51-52, 2008

  6. 29.M. Ponsen, J. Ramon, T. Croonenborghs, K. Driessens, K. Tuyls, Learning of Opponent Models from Incomplete Information in No-Limit Poker, Proceedings of the Annual Belgian-Dutch Machine Learning Conference, Benelearn 2008, Spa, Belgium, (Wehenkel et al., Eds.), pp. 99-100, 2008

  7. 30.T. Croonenborghs, K. Driessens and M. Bruynooghe, Learning a transfer function for reinforcement learning problems, Proceedings of the AAAI-08 Workshop on Transfer Learning for Complex Tasks, Chicago, USA (M. Taylor, K. Driessens and A. Fern eds.) 2008

  8. 31.R. Goetschalckx and K. Driessens, Cost-sensitive reinforcement learning, Proceedings of the workshop on AI Planning and Learning (Kuter, U. and Aberdeen, D. and Buffet, O. and Stone, P., eds.), pp. 1-5, 2007

  9. 32.K. Driessens, J. Ramon and T. Croonenborghs, Transfer Learning for Reinforcement Learning through Goal and Policy Parametrization, Proceedings of the ICML'06 Workshop on Structural Knowledge Transfer for Machine Learning, Pittsburgh, Pennsylvania, USA (B. Banerjee and Y. Liu and G.M. Youngblood, eds.) 2006

  10. 33.K. Driessens and H. Blockeel, Using Predictive Clustering and Probabilistic Constraint Solving for Structural Predictions, Proceedings of the ICML'06 Workshop on Statistical Relational Learning, Pittsburgh, Pennsylvania, USA (A. Fern, L. Getoor and B. Milch, eds.) 2006

  11. 34.P. Tadepalli, R. Givan and K. Driessens, Relational reinforcement learning: an overview, Proceedings of the ICML'04 Workshop on Relational Reinforcement Learning (Tadepalli, P. and Givan, R. and Driessens, K., eds.), pp. 1-9, 2004

  12. 35.J. Ramon and K. Driessens, On the numeric stability of Gaussian processes regression for relational reinforcement learning, ICML-2004 Workshop on Relational Reinforcement Learning (Tadepalli, P. and Givan, R. and Driessens, K., eds.), pp. 10-14, 2004

  13. 36.K. Driessens and S. Dzeroski, On using guidance in relational reinforcement learning, Proceedings of Twelfth Belgian-Dutch Conference on Machine Learning (Wiering, M., ed.), pp. 31-38, 2002

  14. 37.H. Blockeel, K. Driessens, N. Jacobs, R. Kosala, S. Raeymaekers, J. Ramon, J. Struyf, W. Van Laer and S. Verbaeten, First order models for the predictive toxicology challenge, ECML/PKDD Workshop : The Predictive Toxicology Challenge 2000-2001 (Helma, C. and King, R. and Kramer, S. and Srinivasan, A., eds.), pp. 1-12, 2001

  15. 38.K. Driessens, N. Jacobs and B. Robben, KULRoT 1999 Team Description, Team Descriptions of the Robot World Cup Soccer Games and Conference (Coradeshi, S. and Balch, T. and Kraetzschmar, G. and Stone, P., eds.), pp. 69-73, 1999

  16. 39.H. Blockeel, L. Dehaspe, K. Driessens, N. Jacobs, R. Kosala, J. Ramon, and W. Van Laer, The Leuven submission to the Benelearn-99 competition, The Benelearn 1999 Competition (van der Putten, P. and van Someren, M., eds.), pp. 1-8, 1999

  17. 40.N. Jacobs, K. Driessens, and L. De Raedt, Inductive verification and validation of multi agents systems, Proceedings of Workshop on Validation and Verification of Knowledge Based Systems, Trento, Italy (van Harmelen, F., ed.), pp. 1-10, 1998


Contributions at international conferences, not published or only as abstract

  1. 41.K. Driessens, Non-disjount modular boosted policies, Multidisciplinary Symposium on Reinforcement Learning, Montreal, Canada, 2009

  2. 42.S. Sanner, R. Goetschalckx and K. Driessens, Bayesian Search Control for Decision-theoretic Planning 18th International Conference on Automated Planning and Scheduling, Sydney, Australia, presented but unpublished, 2008

  3. 43.L. Antanas, K. Driessens, J. Ramon and T. Croonenborghs, Using Decision Trees as the Answer Networks in Temporal Difference-Networks, 8th European Workshop on Reinforcement Learning, EWRL 2008, Villeneuve d'Ascq, France, 2008

  4. 44.K. Driessens, NPPG: Non-Parametric Policy Gradient, 1st Spring Machine Learning Workshop, SML-08, Traben-Trabach, Germany, 2008

  5. 45.K. Driessens, Using machine learning techniques for single ended line testing, 7th "Freiburg, Leuven and Friends" Workshop on Machine Learning, FLF-06, Titisee, Germany, March 13-14, 2006

  6. 46.K. Driessens and S. Dzeroski, Combining Model-Based and Instance-Based Learning for First Order Regression, 17th Belgian-Dutch Conference on Artificial Intelligence, BNAIC'05, Brussels, Belgium, October 17-18, 2005

  7. 47.K. Driessens, On afterstates and learning tetris, 5th "Freiburg, Leuven and Friends" Workshop on Machine Learning, FLF-04, Hinterzarten, Germany, March 8-10, 2004

  8. 48.K. Driessens, Relational instance based regression for relational reinforcement learning, 4th "Freiburg, Leuven and Friends" Workshop on Machine Learning, FLF-03, Leuven/Dourbes, Belgium, March 19-21, 2003

  9. 49.K. Driessens, and J. Ramon, Relational instance based regression for relational reinforcement learning, 15th Belgian-Dutch Conference on Artificial Intelligence, BNAIC'03, Nijmegen, The Netherlands, October 23-24, 2003

  10. 50.K. Driessens, and S. Dzeroski, Integrating exploration and guidance in relational reinforcement learning, Belgian-Dutch Conference on Artificial Intelligence, BNAIC'02, Leuven, Belgium, October 21-22, 2002

  11. 51.K. Driessens, Adding guidance to relational reinforcement learning, Third Freiburg-Leuven Workshop on Machine Learning, Hinterzarten, Germany, February 27 - March 1, 2002

  12. 52.K. Driessens, and H. Blockeel, Learning digger using hierarchical reinforcement learning for concurrent goals, European Workshop on Reinforcement Learning, EWRL, Utrecht, the Netherlands, October 5-6, 2001

  13. 53.K. Driessens, and H. Blockeel, Learning tetris, 2nd Leuven-Freiburg Workshop on Machine Learning, LF-01, Oostkamp, Belgium, March 14-16, 2001

  14. 54.K. Driessens, J. Ramon, and H. Blockeel, Speeding up relational reinforcement learning through the use of an incremental first order decision tree learner, Belgian-Dutch Artificial Intelligence Conference, BNAIC, Amsterdam, The Netherlands, October 25-26, 2001

  15. 55.K. Driessens, Relational reinforcement learning, Advanced Course on Artificial Intelligence : The Third European Agent Systems Summer School, ACAI, Prague, Czech Republik, July 2-13, 2001

  16. 56.K. Driessens, Relational reinforcement learning, 1st Freiburg-Leuven Workshop on Machine Learning, Freiburg, Germany, April 25-26, 2000


Contributions at other conferences, not published or only as abstract

  1. 57.K. Driessens, Relational reinforcement learning, Industry-Ready Innovative Research: 1st Flanders Engineering PhD Symposium, Brussels, Belgium, December 11, 2003

  2. 58.K. Driessens, Relational reinforcement learning, Faculty of Engineering, PhD Symposium, Leuven, Belgium, December 11, 2002, KUL, Faculty of Engineering


Technical reports

  1. 59.S. Dzeroski, L. De Raedt, and K. Driessens, Relational reinforcement learning, Department of Computer Science, K.U.Leuven, Report CW 311, Leuven, Belgium, May, 2001


Edited books

  1. 60.C. Thurau, K. Driessens and O. Misura, Proceedings of the ICML'10 Workshop on Machine Learning and Games, 2010

  2. 61.J. Ramon, C. Vens, K. Driessens, M. van Otterlo and J. Vanschoren, Proceedings of the Annual Machine Learning Conference of Belgium and The Netherlands, 2010

  3. 62.M. Taylor, K. Driessens and A. Fern, Proceedings of the AAAI'08 Workshop on Transfer Learning for Complex Tasks, 2008

  4. 63.K. Driessens, and A. Fern and M. van Otterlo, Proceedings of the ICML'05 Workshop on Rich Representations for Reinforcement Learning, 2005

  5. 64.P. Tadepalli, and R. Givan, and K. Driessens, Proceedings of the ICML'04 Workshop on Relational Reinforcement Learning, 2004


Bookchapters

  1. 65.K. Driessens, Relational Reinforcement Learning, Encyclopedia of Machine Learning (Sammut, Claude; Webb, Geoffrey I., Eds.), 2010 (in print, due September 29, 2010)

  2. 66.M. Ponsen, T. Croonenborghs, K. Tuyls, J. Ramon, K. Driessens, J. van den Herik, and E. Postma, Learning with whom to communicate using relational reinforcement learning, Interactive Collaborative Information Systems (Babuska, Robert; Groen, Frans C.A., Eds.), Studies in Computational Intelligence , vol. 281, Springer, 2010, pp. 45-64

  3. 67.K. Driessens, Relational reinforcement learning, Multi-Agent Systems and Applications, (Luck, Michael and Marik, Vladimir and Trappl, Robert and Stepankova, Olga, eds.), vol. 2086, Lecture Notes in Artificial Intelligence, Springer-Verlag, 2001, pp.271-280


Thesis

  1. 68.K. Driessens, Relational reinforcement learning, Ph.D. Thesis, Department of Computer Science, K.U.Leuven, Leuven, Belgium, May, 2004, 222 + xx pages

  2. 69.K. Driessens, Statistische Onderbouwing van Database Ontginning. (translation: Statistical support for Knowledge Discovery in Databases), Masters Thesis, Department of Computer Science, K.U.Leuven, Leuven, Belgium, June 1997.