Inductive verification and validation of multi agent systems. - Nico Jacobs; Kurt Driessens; Luc De Raedt (EUROVAV, 1998)

Using ILP-Systems for Verification and Validation of Multi-agent Systems. - Nico Jacobs; Kurt Driessens; Luc De Raedt (ILP, 1998)

Inductive Verification and Validation of the KULRoT RoboCup Team. - Kurt Driessens; Nico Jacobs; Nathalie Cossement; Patrick Monsieurs; Luc De Raedt (RoboCup, 1998)

Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner. - Kurt Driessens; Jan Ramon; Hendrik Blockeel (ECML, 2001)

Relational Reinforcement Learning. - Saso Dzeroski; Luc De Raedt; Kurt Driessens (Mach. Learn., 2001)

Integrating Experimentation and Guidance in Relational Reinforcement Learning. - Kurt Driessens; Saso Dzeroski (ICML, 2002)

Relational Instance Based Regression for Relational Reinforcement Learning. - Kurt Driessens; Jan Ramon (ICML, 2003)

Integrating Guidance into Relational Reinforcement Learning. - Kurt Driessens; Saso Dzeroski (Mach. Learn., 2004)

Combining model-based and instance-based learning for first order regression. - Kurt Driessens; Saso Dzeroski (ICML, 2005)

Relational reinforcement learning. - Kurt Driessens (AI Commun., 2005)

Using Weighted Nearest Neighbor to Benefit from Unlabeled Data. - Kurt Driessens; Peter Reutemann; Bernhard Pfahringer; Claire Leschi (PAKDD, 2006)

Graph kernels and Gaussian processes for relational reinforcement learning. - Kurt Driessens; Jan Ramon; Thomas Gärtner 001 (Mach. Learn., 2006)

Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling. - Jan Ramon; Kurt Driessens; Tom Croonenborghs (ECML, 2007)

Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning. - Tom Croonenborghs; Kurt Driessens; Maurice Bruynooghe (ILP, 2007)

Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker. - Marc J. V. Ponsen; Jan Ramon; Tom Croonenborghs; Kurt Driessens; Karl Tuyls (AAAI, 2008)

Using Decision Trees as the Answer Networks in Temporal Difference-Networks. - Laura-Andreea Antanas; Kurt Driessens; Jan Ramon; Tom Croonenborghs (ECAI, 2008)

Reinforcement Learning with the Use of Costly Features. - Robby Goetschalckx; Scott Sanner; Kurt Driessens (ECAI, 2008)

Cost-Sensitive Parsimonious Linear Regression. - Robby Goetschalckx; Kurt Driessens; Scott Sanner (ICDM, 2008)

Non-parametric policy gradients: a unified treatment of propositional and relational domains. - Kristian Kersting; Kurt Driessens (ICML, 2008)

Monte-Carlo Tree Search in Poker Using Expected Reward Distributions. - Guy Van den Broeck; Kurt Driessens; Jan Ramon (ACML, 2009)

Learning with whom to communicate using relational reinforcement learning. - Marc J. V. Ponsen; Tom Croonenborghs; Karl Tuyls; Jan Ramon; Kurt Driessens (AAMAS (2), 2009)

Bayesian Real-Time Dynamic Programming. - Scott Sanner; Robby Goetschalckx; Kurt Driessens; Guy Shani (IJCAI, 2009)

Relational Reinforcement Learning. - Kurt Driessens (Encyclopedia of Machine Learning, 2010)

Learning with Whom to Communicate Using Relational Reinforcement Learning. - Marc J. V. Ponsen; Tom Croonenborghs; Karl Tuyls; Jan Ramon; Kurt Driessens; H. Jaap van den Herik; Eric O. Postma (Interactive Collaborative Information Systems, 2010)

Using the online cross-entropy method to learn relational policies for playing different games. - Samuel Sarjant; Bernhard Pfahringer; Kurt Driessens; Tony Smith (CIG, 2011)

Adaptive Windowing for Online Learning from Multiple Inter-related Data Streams. - Elena Ikonomovska; Kurt Driessens; Saso Dzeroski; João Gama 001 (ICDM Workshops, 2011)

Reinforcement learning transfer via sparse coding. - Haitham Bou-Ammar; Karl Tuyls; Matthew E. Taylor; Kurt Driessens; Gerhard Weiss 001 (AAMAS, 2012)

A Direct Policy-Search Algorithm for Relational Reinforcement Learning. - Samuel Sarjant; Bernhard Pfahringer; Kurt Driessens; Tony Smith (ILP, 2013)

Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines. - Haitham Bou-Ammar; Decebal Constantin Mocanu; Matthew E. Taylor; Kurt Driessens; Karl Tuyls; Gerhard Weiss 001 (ECML/PKDD (2), 2013)

Largest Source Subset Selection for Instance Transfer. - Shuang Zhou 001; Gijs Schoenmakers; Evgueni N. Smirnov; Ralf Peeters; Kurt Driessens; Siqi Chen 001 (ACML, 2015)

A Non-parametric Conformity-Based Test for Transfer Decisions. - Shuang Zhou 001; Evgueni N. Smirnov; Gijs Schoenmakers; Ralf Peeters; Kurt Driessens (ICTAI, 2015)

Factored four way conditional restricted Boltzmann machines for activity recognition. - Decebal Constantin Mocanu; Haitham Bou-Ammar; Dietwig Lowet; Kurt Driessens; Antonio Liotta; Gerhard Weiss 001; Karl Tuyls (Pattern Recognit. Lett., 2015)

A Data Driven Similarity Measure and Example Mapping Function for General, Unlabelled Data Sets. - Damien Lejeune; Kurt Driessens (ECAI, 2016)

A Wavelet-based Encoding for Neuroevolution. - Sjoerd van Steenkiste; Jan Koutník; Kurt Driessens; Jürgen Schmidhuber (GECCO, 2016)

Simultaneous Ensemble Generation and Hyperparameter Optimization for Regression. - David Roschewitz; Kurt Driessens; Pieter Collins (BNCAI, 2017)

Detection of Atrial Fibrillation Episodes from Short Single Lead Recordings by Means of Ensemble Learning. - Pietro Bonizzi; Kurt Driessens; Joël M. H. Karel (CinC, 2017)

UMAP 2017 EdRecSys Workshop Organizers' Welcome & Organization. - Kurt Driessens; Irena Koprinska; Olga C. Santos; Evgueni N. Smirnov; Kalina Yacef; Osmar R. Zaïane (UMAP (Adjunct Publication), 2017)

Discovering Hidden Course Requirements and Student Competences from Grade Data. - Mara Houbraken; Chang Sun 001; Evgueni N. Smirnov; Kurt Driessens (UMAP (Adjunct Publication), 2017)

Introduction to the special issue dedicated to the Journal Track of ECML PKDD 2017. - Kurt Driessens; Dragi Kocev; Marko Robnik-Sikonja; Myra Spiliopoulou (Mach. Learn., 2017)

Testing exchangeability for transfer decision. - Shuang Zhou 001; Evgueni N. Smirnov; Gijs Schoenmakers; Kurt Driessens; Ralf Peeters (Pattern Recognit. Lett., 2017)

Relational Reinforcement Learning. - Kurt Driessens (Encyclopedia of Machine Learning and Data Mining, 2017)

Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees. - Dennis J. N. J. Soemers; Tim Brys; Kurt Driessens; Mark H. M. Winands; Ann Nowé (AAAI, 2018)

A Generative Policy Gradient Approach for Learning to Play Text-Based Adventure Games. - René Raab; Kurt Driessens (BNAIC/BENELEARN, 2019)

Contextual encoder-decoder network for visual saliency prediction. - Alexander Kroner; Mario Senden; Kurt Driessens; Rainer Goebel (Neural Networks, 2020)

Biologically Inspired Semantic Lateral Connectivity for Convolutional Neural Networks. - Tonio Weidler; Julian Lehnen; Quinton Denman; Dávid Sebok; Gerhard Weiss 001; Kurt Driessens; Mario Senden (CoRR, 2021)

A quantum algorithm for track reconstruction in the LHCb vertex detector. - Davide Nicotra; Miriam Lucio Martinez; Jacco Andreas de Vries; Marcel Merk; Kurt Driessens; Ronald Leonard Westra; Domenica Dibenedetto; Daniel Hugo Cámpora Pérez (CoRR, 2023)

Towards a Characterisation of Monte-Carlo Tree Search Performance in Different Games. - Dennis J. N. J. Soemers; Guillaume Bams; Max Persoon; Marco Rietjens; Dimitar Sladic; Stefan Stefanov; Kurt Driessens; Mark H. M. Winands (CoG, 2024)

Concept Basis Extraction for Latent Space Interpretation of Image Classifiers. - Alexandros Doumanoglou; Dimitrios Zarpalas; Kurt Driessens (VISIGRAPP (3): VISAPP, 2024)

Environment Descriptions for Usability and Generalisation in Reinforcement Learning. - Dennis J. N. J. Soemers; Spyridon Samothrakis; Kurt Driessens; Mark H. M. Winands (ICAART (3), 2025)

Deep learning based estimation of heart surface potentials. - Tiantian Wang; Joël M. H. Karel; Niels Osnabrugge; Kurt Driessens; Job Stoks; Matthijs J. M. Cluitmans; Paul G. A. Volders; Pietro Bonizzi; Ralf L. M. Peeters (Artif. Intell. Medicine, 2025)