Thomas Gabel
Thomas Gabel
Professor at Frankfurt University of Applied Sciences
Verified email at - Homepage
Cited by
Cited by
Batch reinforcement learning
S Lange, T Gabel, M Riedmiller
Reinforcement learning, 45-73, 2012
Reinforcement learning for robot soccer
M Riedmiller, T Gabel, R Hafner, S Lange
Autonomous Robots 27 (1), 55-73, 2009
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
Adaptive reactive job-shop scheduling with reinforcement learning agents
T Gabel, M Riedmiller
International Journal of Information Technology and Intelligent Computing 24 …, 2008
Using evolution programs to learn local similarity measures
A Stahl, T Gabel
International Conference on Case-Based Reasoning, 537-551, 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
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
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
Distributed policy search reinforcement learning for job-shop scheduling tasks
T Gabel, M Riedmiller
International Journal of production research 50 (1), 41-61, 2012
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
D3. 1.1. a: KAON–ontology management infrastructure
T Gabel, Y Sure, J Voelker
SEKT informal deliverable, 2004
Parameters optimization of support vector machines for imbalanced data using social ski driver algorithm
A Tharwat, T Gabel
Neural computing and applications 32 (11), 6925-6938, 2020
Cbr for state value function approximation in reinforcement learning
T Gabel, M Riedmiller
International Conference on Case-Based Reasoning, 206-221, 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
Parameter optimization of support vector machine using dragonfly algorithm
A Tharwat, T Gabel, AE Hassanien
International conference on advanced intelligent systems and informatics …, 2017
Multi-Agent Reinforcement Learning Approaches for Distributed Job-Shop Scheduling Problems
T Gabel
University of Osnabrueck, 2009
Learning a Partial Behavior for a Competitive Robotic Soccer Agent.
T Gabel, MA Riedmiller
Künstliche Intell. 20 (2), 18-23, 2006
Exploiting background knowledge when learning similarity measures
T Gabel, A Stahl
European Conference on Case-Based Reasoning, 169-183, 2004
Brainstormers 2D–Team Description 2005
M Riedmiller, T Gabel, J Knabe, H Strasdat
RoboCup, 219-229, 2005
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
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