Reinforcement learning for robot soccer M Riedmiller, T Gabel, R Hafner, S Lange Autonomous Robots 27 (1), 55-73, 2009 | 238 | 2009 |
Batch reinforcement learning S Lange, T Gabel, M Riedmiller Reinforcement learning, 45-73, 2012 | 113 | 2012 |
Using evolution programs to learn local similarity measures A Stahl, T Gabel International Conference on Case-Based Reasoning, 537-551, 2003 | 82 | 2003 |
On experiences in a complex and competitive gaming domain: Reinforcement learning meets robocup M Riedmiller, T Gabel 2007 IEEE Symposium on Computational Intelligence and Games, 17-23, 2007 | 68 | 2007 |
Intelligent Bézier curve-based path planning model using Chaotic Particle Swarm Optimization algorithm A Tharwat, M Elhoseny, AE Hassanien, T Gabel, A Kumar Cluster Computing 22 (2), 4745-4766, 2019 | 64 | 2019 |
D3. 1.1. a: KAON–ontology management infrastructure T Gabel, Y Sure, J Voelker SEKT informal deliverable, 2004 | 55 | 2004 |
A case study on improving defense behavior in soccer simulation 2D: The NeuroHassle approach T Gabel, M Riedmiller, F Trost Robot Soccer World Cup, 61-72, 2008 | 50 | 2008 |
Adaptive reactive job-shop scheduling with reinforcement learning agents T Gabel, M Riedmiller International Journal of Information Technology and Intelligent Computing 24 (4), 2008 | 50 | 2008 |
CBR for state value function approximation in reinforcement learning T Gabel, M Riedmiller International Conference on Case-Based Reasoning, 206-221, 2005 | 45 | 2005 |
On a successful application of multi-agent reinforcement learning to operations research benchmarks T Gabel, M Riedmiller 2007 IEEE International Symposium on Approximate Dynamic Programming and …, 2007 | 35 | 2007 |
Learning a Partial Behavior for a Competitive Robotic Soccer Agent. T Gabel, MA Riedmiller KI 20 (2), 18-23, 2006 | 32 | 2006 |
Exploiting background knowledge when learning similarity measures T Gabel, A Stahl European Conference on Case-Based Reasoning, 169-183, 2004 | 30 | 2004 |
Brainstormers 2D–Team Description 2005 M Riedmiller, T Gabel, J Knabe, H Strasdat RoboCup, 219-229, 2005 | 28 | 2005 |
On progress in RoboCup: the simulation league showcase T Gabel, M Riedmiller Robot Soccer World Cup, 36-47, 2010 | 27 | 2010 |
Bridging the gap: Learning in the RoboCup simulation and midsize league T Gabel, R Hafner, S Lange, M Lauer, M Riedmiller Proceedings of the 7th Portuguese Conference on Automatic Control, 2006 | 27 | 2006 |
MOGOA algorithm for constrained and unconstrained multi-objective optimization problems A Tharwat, EH Houssein, MM Ahmed, AE Hassanien, T Gabel Applied Intelligence 48 (8), 2268-2283, 2018 | 24 | 2018 |
Distributed policy search reinforcement learning for job-shop scheduling tasks T Gabel, M Riedmiller International Journal of production research 50 (1), 41-61, 2012 | 24 | 2012 |
Multi-Agent Reinforcement Learning Approaches for Distributed Job-Shop Scheduling Problems T Gabel University of Osnabrueck, 2009 | 22 | 2009 |
Optimizing similarity assessment in case-based reasoning A Stahl, T Gabel PROCEEDINGS OF THE NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE 21 (2), 1667, 2006 | 22 | 2006 |
Advances in case-based reasoning KD Althoff, R Bergmann, M Minor, A Hanft Springer, 2008 | 20 | 2008 |