José Antonio Martín H.
José Antonio Martín H.
Repsol Technology Lab
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Dyna-H: A heuristic planning reinforcement learning algorithm applied to role-playing game strategy decision systems
JA Martin H., M Santos, V López, G Botella
Knowledge-Based Systems 32, 28-36, 2012
Adaptation, anticipation and rationality in natural and artificial systems: computational paradigms mimicking nature
JA Martin H., J de Lope, D Maravall
Natural Computing 8 (4), 757, 2009
Orthogonal variant moments features in image analysis
JA Martin H., M Santos, J de Lope
Information Sciences 180 (6), 846-860, 2010
Robust high performance reinforcement learning through weighted k-nearest neighbors
JA Martin H., J de Lope, D Maravall
Neurocomputing 74 (8), 1251-1259, 2011
A method to learn the inverse kinematics of multi-link robots by evolving neuro-controllers
JA Martín H, J de Lope, M Santos
Neurocomputing 72 (13), 2806-2814, 2009
FPGA-based multimodal embedded sensor system integrating low-and mid-level vision
G Botella, JA Martín H, M Santos, U Meyer-Baese
Sensors 11 (8), 8164-8179, 2011
Hybridizing evolutionary computation and reinforcement learning for the design of almost universal controllers for autonomous robots
D Maravall, J de Lope, JA Martín H
Neurocomputing 72 (4-6), 887-894, 2009
The knn-td reinforcement learning algorithm
JA Martin H., J de Lope, D Maravall
International Work-Conference on the Interplay Between Natural and …, 2009
Search and retrieval of plasma wave forms: Structural pattern recognition approach
S Dormido-Canto, G Farias, J Vega, R Dormido, J Sánchez, N Duro, ...
Review of scientific instruments 77 (10), 2006
A distributed reinforcement learning architecture for multi-link robots
JA Martin H, J De Lope
4th International Conference on Informatics in Control, Automation and …, 2007
Learning autonomous helicopter flight with evolutionary reinforcement learning
JA Martin H., J de Lope
International Conference on Computer Aided Systems Theory, 75-82, 2009
Ex〈 α〉: An effective algorithm for continuous actions Reinforcement Learning problems
JA Martin H, J de Lope
Industrial Electronics, 2009. IECON'09. 35th Annual Conference of IEEE, 2063 …, 2009
Analysis and solution of a predator–protector–prey multi-robot system by a high-level reinforcement learning architecture and the adaptive systems theory
JA Martin H., J de Lope, D Maravall
Robotics and Autonomous Systems 58 (12), 1266-1272, 2010
A divisive hierarchical k-means based algorithm for image segmentation
JA Martin H, J Montero, J Yáñez, D Gomez
Intelligent Systems and Knowledge Engineering (ISKE), 2010 International …, 2010
Modelo computacional para la formación de clases de equivalencia
AG García, JA Martín H., MTG Domínguez
International Journal of Psychology and Psychological Therapy 10 (1), 163-176, 2010
Linear Bayes policy for learning in contextual-bandits
JA Martín H., AM Vargas
Expert Systems with Applications 40 (18), 7400–7406, 2013
Dynamic clustering and modeling approaches for fusion plasma signals
JA Martin H, MS Penas, G Farias, N Duro, J Sanchez, R Dormido, ...
Instrumentation and Measurement, IEEE Transactions on 58 (9), 2969-2978, 2009
Applying reinforcement learning to multi-robot team coordination
Y Sanz, J de Lope, JA Martin H.
International Workshop on Hybrid Artificial Intelligence Systems, 625-632, 2008
Evolution of Neuro-controllers for Multi-link Robots
JA Martín H, J de Lope, M Santos
Innovations in Hybrid Intelligent Systems, 175-182, 2007
Solving Hard Computational Problems Efficiently: Asymptotic Parametric Complexity 3-Coloring Algorithm
JA Martın H
PLoS ONE 8 (1), e53437, 2013
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