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Kurt Driessens: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Kurt Driessens, Saso Dzeroski
    Combining Model-Based and Instance-Based Learning for First Order Regression. [Citation Graph (0, 0)][DBLP]
    BNAIC, 2005, pp:341-342 [Conf]
  2. Kurt Driessens
    Relational Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    EASSS, 2001, pp:271-280 [Conf]
  3. Kurt Driessens, Jan Ramon, Hendrik Blockeel
    Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner. [Citation Graph (0, 0)][DBLP]
    ECML, 2001, pp:97-108 [Conf]
  4. Kurt Driessens, Saso Dzeroski
    Integrating Experimentation and Guidance in Relational Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2002, pp:115-122 [Conf]
  5. Kurt Driessens, Saso Dzeroski
    Combining model-based and instance-based learning for first order regression. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:193-200 [Conf]
  6. Kurt Driessens, Jan Ramon
    Relational Instance Based Regression for Relational Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:123-130 [Conf]
  7. Thomas Gärtner, Kurt Driessens, Jan Ramon
    Graph Kernels and Gaussian Processes for Relational Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ILP, 2003, pp:146-163 [Conf]
  8. Nico Jacobs, Kurt Driessens, Luc De Raedt
    Using ILP-Systems for Verification and Validation of Multi-agent Systems. [Citation Graph (0, 0)][DBLP]
    ILP, 1998, pp:145-154 [Conf]
  9. Kurt Driessens, Peter Reutemann, Bernhard Pfahringer, Claire Leschi
    Using Weighted Nearest Neighbor to Benefit from Unlabeled Data. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2006, pp:60-69 [Conf]
  10. Kurt Driessens, Nico Jacobs, Nathalie Cossement, Patrick Monsieurs, Luc De Raedt
    Inductive Verification and Validation of the KULRoT RoboCup Team. [Citation Graph (0, 0)][DBLP]
    RoboCup, 1998, pp:193-206 [Conf]
  11. Kurt Driessens
    Relational reinforcement learning. [Citation Graph (0, 0)][DBLP]
    AI Commun., 2005, v:18, n:1, pp:71-73 [Journal]
  12. Kurt Driessens, Saso Dzeroski
    Integrating Guidance into Relational Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2004, v:57, n:3, pp:271-304 [Journal]
  13. Saso Dzeroski, Luc De Raedt, Kurt Driessens
    Relational Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2001, v:43, n:1/2, pp:7-52 [Journal]
  14. Kurt Driessens, Jan Ramon, Thomas Gärtner
    Graph kernels and Gaussian processes for relational reinforcement learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2006, v:64, n:1-3, pp:91-119 [Journal]
  15. Jan Ramon, Kurt Driessens, Tom Croonenborghs
    Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling. [Citation Graph (0, 0)][DBLP]
    ECML, 2007, pp:699-707 [Conf]

  16. Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker. [Citation Graph (, )][DBLP]


  17. Learning with whom to communicate using relational reinforcement learning. [Citation Graph (, )][DBLP]


  18. Reinforcement Learning with the Use of Costly Features. [Citation Graph (, )][DBLP]


  19. Using Decision Trees as the Answer Networks in Temporal Difference-Networks. [Citation Graph (, )][DBLP]


  20. Cost-Sensitive Parsimonious Linear Regression. [Citation Graph (, )][DBLP]


  21. Non-parametric policy gradients: a unified treatment of propositional and relational domains. [Citation Graph (, )][DBLP]


  22. Bayesian Real-Time Dynamic Programming. [Citation Graph (, )][DBLP]


  23. Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning. [Citation Graph (, )][DBLP]


  24. Reinforcement Learning with the Use of Costly Features. [Citation Graph (, )][DBLP]


  25. Monte-Carlo Tree Search in Poker Using Expected Reward Distributions. [Citation Graph (, )][DBLP]


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