Local Coordination in Online Distributed Constraint Optimization Problems. - Tim Brys; Yann-Michaël De Hauwere; Ann Nowé; Peter Vrancx (EUMAS, 2011)

Improving Convergence of CMA-ES Through Structure-Driven Discrete Recombination. - Tim Brys; Ann Nowé (AAAI, 2012)

Meta-Evolutionary Algorithms and recombination operators for satisfiability solving in fuzzy logics. - Tim Brys; Madalina M. Drugan; Ann Nowé (IEEE Congress on Evolutionary Computation, 2013)

Solving satisfiability in fuzzy logics by mixing CMA-ES. - Tim Brys; Madalina M. Drugan; Peter A. N. Bosman; Martine De Cock; Ann Nowé (GECCO, 2013)

Local search and restart strategies for satisfiability solving in fuzzy logics. - Tim Brys; Madalina M. Drugan; Peter A. N. Bosman; Martine De Cock; Ann Nowé (GEFS, 2013)

On the Behaviour of Scalarization Methods for the Engagement of a Wet Clutch. - Tim Brys; Kristof Van Moffaert; Kevin Van Vaerenbergh; Ann Nowé (ICMLA (1), 2013)

Reinforcement Learning on Multiple Correlated Signals. - Tim Brys; Ann Nowé (AAAI, 2014)

Combining Multiple Correlated Reward and Shaping Signals by Measuring Confidence. - Tim Brys; Ann Nowé; Daniel Kudenko; Matthew E. Taylor (AAAI, 2014)

Adaptive objective selection for correlated objectives in multi-objective reinforcement learning. - Tim Brys; Kristof Van Moffaert; Ann Nowé; Matthew E. Taylor (AAMAS, 2014)

Designing reusable metaheuristic methods: A semi-automated approach. - Steven Adriaensen; Tim Brys; Ann Nowé (IEEE Congress on Evolutionary Computation, 2014)

Using Ensemble Techniques and Multi-Objectivization to Solve Reinforcement Learning Problems. - Tim Brys; Matthew E. Taylor; Ann Nowé (ECAI, 2014)

Off-Policy Shaping Ensembles in Reinforcement Learning. - Anna Harutyunyan; Tim Brys; Peter Vrancx; Ann Nowé (ECAI, 2014)

Fair-share ILS: a simple state-of-the-art iterated local search hyperheuristic. - Steven Adriaensen; Tim Brys; Ann Nowé (GECCO, 2014)

Multi-objectivization of reinforcement learning problems by reward shaping. - Tim Brys; Anna Harutyunyan; Peter Vrancx; Matthew E. Taylor; Daniel Kudenko; Ann Nowé (IJCNN, 2014)

A novel adaptive weight selection algorithm for multi-objective multi-agent reinforcement learning. - Kristof Van Moffaert; Tim Brys; Arjun Chandra; Lukas Esterle; Peter R. Lewis 001; Ann Nowé (IJCNN, 2014)

Student travel award recipients for the 2014 AAAI/SIGAI doctoral consortium. - Tim Brys; John Doucette 002; Taraneh Khazaei; Ran Taig (AI Matters, 2014)

Distributed learning and multi-objectivity in traffic light control. - Tim Brys; Tong T. Pham; Matthew E. Taylor (Connect. Sci., 2014)

Policy Transfer using Reward Shaping. - Tim Brys; Anna Harutyunyan; Matthew E. Taylor; Ann Nowé (AAMAS, 2015)

Multi-Scale Reward Shaping via an Off-Policy Ensemble. - Anna Harutyunyan; Tim Brys; Peter Vrancx; Ann Nowé (AAMAS, 2015)

Shaping Mario with Human Advice. - Anna Harutyunyan; Tim Brys; Peter Vrancx; Ann Nowé (AAMAS, 2015)

Risk-sensitivity through multi-objective reinforcement learning. - Kristof Van Moffaert; Tim Brys; Ann Nowé (CEC, 2015)

Online Distributed Voltage Control of an offshore MTdc network using reinforcement learning. - S. Rodrigues; Rodrigo Teixeira Pinto; Pavol Bauer; Tim Brys; Ann Nowé (CEC, 2015)

Encoding and Combining Knowledge to Speed up Reinforcement Learning. - Tim Brys (IJCAI, 2015)

Reinforcement Learning from Demonstration through Shaping. - Tim Brys; Anna Harutyunyan; Halit Bener Suay; Sonia Chernova; Matthew E. Taylor; Ann Nowé (IJCAI, 2015)

Departure MANagement with a Reinforcement Learning Approach: Respecting CFMU Slots. - Ivomar Brito Soares; Yann-Michaël De Hauwere; Kris Januarius; Tim Brys; Thierry Salvant; Ann Nowé (ITSC, 2015)

Using PCA to Efficiently Represent State Spaces. - William Curran; Tim Brys; Matthew E. Taylor; William D. Smart (CoRR, 2015)

Off-Policy Reward Shaping with Ensembles. - Anna Harutyunyan; Tim Brys; Peter Vrancx; Ann Nowé (CoRR, 2015)

Dimensionality Reduced Reinforcement Learning for Assistive Robots. - William Curran; Tim Brys; David W. Aha; Matthew E. Taylor; William D. Smart (AAAI Fall Symposia, 2016)

Learning from Demonstration for Shaping through Inverse Reinforcement Learning. - Halit Bener Suay; Tim Brys; Matthew E. Taylor; Sonia Chernova (AAMAS, 2016)

A Gentle Introduction to Reinforcement Learning. - Ann Nowé; Tim Brys (SUM, 2016)

Multi-objectivization and ensembles of shapings in reinforcement learning. - Tim Brys; Anna Harutyunyan; Peter Vrancx; Ann Nowé; Matthew E. Taylor (Neurocomputing, 2017)

Preface to the special issue: adaptive and learning agents. - Daan Bloembergen; Tim Brys; Logan Yliniemi (Knowl. Eng. Rev., 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)

Introspective Reinforcement Learning and Learning from Demonstration. - Mao Li; Tim Brys; Daniel Kudenko (AAMAS, 2018)

Directed Policy Gradient for Safe Reinforcement Learning with Human Advice. - Hélène Plisnier; Denis Steckelmacher; Tim Brys; Diederik M. Roijers; Ann Nowé (CoRR, 2018)

Introspective Q-learning and learning from demonstration. - Mao Li; Tim Brys; Daniel Kudenko (Knowl. Eng. Rev., 2019)

A conceptual framework for externally-influenced agents: an assisted reinforcement learning review. - Adam Bignold; Francisco Cruz 002; Matthew E. Taylor; Tim Brys; Richard Dazeley; Peter Vamplew 001; Cameron Foale (J. Ambient Intell. Humaniz. Comput., 2023)