Practical Issues in Temporal Difference Learning
Machine Learning
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Least-squares policy iteration
The Journal of Machine Learning Research
Tree-Based Batch Mode Reinforcement Learning
The Journal of Machine Learning Research
Evolutionary Function Approximation for Reinforcement Learning
The Journal of Machine Learning Research
Empirical Studies in Action Selection with Reinforcement Learning
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Batch reinforcement learning in a complex domain
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Model-based function approximation in reinforcement learning
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Non-parametric policy gradients: a unified treatment of propositional and relational domains
Proceedings of the 25th international conference on Machine learning
Finite-Time Bounds for Fitted Value Iteration
The Journal of Machine Learning Research
Rollout sampling approximate policy iteration
Machine Learning
Reinforcement learning for DEC-MDPs with changing action sets and partially ordered dependencies
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
An Analysis of Case-Based Value Function Approximation by Approximating State Transition Graphs
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Fitted Natural Actor-Critic: A New Algorithm for Continuous State-Action MDPs
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Recent Advances in Reinforcement Learning
Gaussian process dynamic programming
Neurocomputing
Learning complex motions by sequencing simpler motion templates
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Reinforcement learning for robot soccer
Autonomous Robots
Sample-efficient evolutionary function approximation for reinforcement learning
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Compositional Models for Reinforcement Learning
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Reinforcement learning versus model predictive control: a comparison on a power system problem
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive autonomous control using online value iteration with Gaussian processes
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Using continuous action spaces to solve discrete problems
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Neural dynamic programming based temperature optimal control for cement calcined process
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Autonomous Agents and Multi-Agent Systems
Reinforcement learning based neural controllers for dynamic processes without exploration
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
Hessian matrix distribution for Bayesian policy gradient reinforcement learning
Information Sciences: an International Journal
Sequential feature selection for classification
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
Reinforcement learning with a bilinear q function
EWRL'11 Proceedings of the 9th European conference on Recent Advances in Reinforcement Learning
Learn to swing up and balance a real pole based on raw visual input data
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
Machine learning for interactive systems and robots: a brief introduction
Proceedings of the 2nd Workshop on Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action and Communication
Proceedings of the 19th international conference on Intelligent User Interfaces
| Hi-index | 0.00 |
This paper introduces NFQ, an algorithm for efficient and effective training of a Q-value function represented by a multi-layer perceptron. Based on the principle of storing and reusing transition experiences, a model-free, neural network based Reinforcement Learning algorithm is proposed. The method is evaluated on three benchmark problems. It is shown empirically, that reasonably few interactions with the plant are needed to generate control policies of high quality.