PhD theses


Lara Verheyen, Procedural Semantics for Human-like Language Understanding in Situated Environments

Mathieu Reymond, On incorporating prior knowledge about the decision maker in multi-objective reinforcement learning

Hélène Plisnier, Guiding the Exploration Strategy of a Reinforcement Learning Agent


Jens Nevens, Representing and Learning Linguistic Structures on the Conceptual, Morpho-Syntactic and Semantic Level

Simon Marynissen, Advances in Justification Theory


Sabine van der Ham, Investigating Cognitive and Functional Biases for Learning Acoustic Categories

Roxana Rădulescu, Decision Making in Multi-Objective Multi-Agent Systems

Timothy Verstraeten, Multi-Agent Reinforcement Learning Approach to Wind Farm Control


Elias Fernández Domingos, Coordinating Human and Agent Behavior in Collective Risk Scenarios

Denis Steckelmacher, Model-Free Reinforcement Learning for Real-World Robots

Isel Grau, Self-labeling Grey-Box Model: An Interpretable Semi-Supervised Classifier

Pieter Libin, Guiding the mitigation of epidemics with reinforcement learning


Felipe Gomez Marulanda, Automated 3D geometry segmentations for Computational Fluid Dynamics applications


Steven Adriaensen, On the Semi-automated Design of Reusable Heuristics with applications to hard combinatorial optimization

Paul Van Eecke, Generalisation and Specialisation Operators for Computational Construction Grammar and their Application in Evolutionary Linguistics Research

Anna Harutyunyan, Beyond Single-Step Temporal Difference Learning


Kristof van Moffaert, Multi-Criteria Reinforcement Learning for Sequential Decision Making Problems

Tim Brys, Reinforcement Learning from Heuristic Information


David Catteeuw, Emergence of Honest Signaling through Learning and Evolution


Marjon Blondeel, Nonmonotonic Reasoning in Multivalued Logics


Katrien Beuls, Towards an agent-based tutoring system for Spanish verb conjugation

Yunierkis Perez-Castillo, Computational design of novel FabH inhibitors as potential antibacterial agents

Abdel Rodriguez Abed, Continuous Action Reinforcement Learning Automata, an RL technique for controlling production machines


Mihail Mihaylov, Decentralized Coordination in Multi-Agent Systems

Jonatan Taminau, Unlocking the potential of public available gene expression data for large-scale analysis

Yailen Martinez, A Generic Multi-Agent Reinforcement Learning Approach for Scheduling Problems

Nashat Abughalieh, Source and channel coding in wireless sensor networks


Yann-Michaël De Hauwere, Sparse Interactions in Multi-Agent Reinforcement Learning


Walter Colitti, Multi-layer Traffic Engineering in the New Generation Internet Based on IP/MPLS over ASON/GMPLS networks

Sven Van Segbroeck, Complex dynamics in adaptive networks

Peter Vrancx, Decentralized Reinforcement Learning in Markov Games