| Reinforcement learning for robot soccer M Riedmiller, T Gabel, R Hafner, S Lange Autonomous Robots 27 (1), 55-73, 2009 | 269 | 2009 |
| Batch reinforcement learning S Lange, T Gabel, M Riedmiller Reinforcement learning, 45-73, 2012 | 165 | 2012 |
| Using evolution programs to learn local similarity measures A Stahl, T Gabel International Conference on Case-Based Reasoning, 537-551, 2003 | 80 | 2003 |
| 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 | 79 | 2019 |
| 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 | 71 | 2007 |
| Adaptive reactive job-shop scheduling with reinforcement learning agents T Gabel, M Riedmiller International Journal of Information Technology and Intelligent Computing 24 …, 2008 | 58 | 2008 |
| 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 | 54 | 2008 |
| CBR for state value function approximation in reinforcement learning T Gabel, M Riedmiller International Conference on Case-Based Reasoning, 206-221, 2005 | 48 | 2005 |
| Classification of toxicity effects of biotransformed hepatic drugs using whale optimized support vector machines A Tharwat, YS Moemen, AE Hassanien Journal of biomedical informatics 68, 132-149, 2017 | 41 | 2017 |
| 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 | 40 | 2007 |
| 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 | 35 | 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 | 34 | 2012 |
| Learning a Partial Behavior for a Competitive Robotic Soccer Agent. T Gabel, MA Riedmiller KI 20 (2), 18-23, 2006 | 33 | 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 |
| Multi-Agent Reinforcement Learning Approaches for Distributed Job-Shop Scheduling Problems T Gabel University of Osnabrueck, 2009 | 27 | 2009 |
| 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 |
| Improved neural fitted Q iteration applied to a novel computer gaming and learning benchmark T Gabel, C Lutz, M Riedmiller 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement …, 2011 | 23 | 2011 |
Sascha LangePSIORIDirección de correo verificada de psiori.com
