Model-based control of a robot manipulator
Model-based control of a robot manipulator
Proceedings of the seventh international conference (1990) on Machine learning
Automatic programming of behavior-based robots using reinforcement learning
Artificial Intelligence
Incremental multi-step Q-learning
Machine Learning - Special issue on reinforcement learning
Purposive behavior acquisition for a real robot by vision-based reinforcement learning
Machine Learning - Special issue on robot learning
A Kendama learning robot based on bi-directional theory
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
Using expectation-maximization for reinforcement learning
Neural Computation
Locally Weighted Learning for Control
Artificial Intelligence Review - Special issue on lazy learning
Learning agents for uncertain environments (extended abstract)
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
A framework for reinforcement learning on real robots
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Nonparametric model-based reinforcement learning
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Likelilood ratio gradient estimation: an overview
WSC '87 Proceedings of the 19th conference on Winter simulation
Practical methods for optimal control using nonlinear programming
Practical methods for optimal control using nonlinear programming
Dynamic Programming and Optimal Control
Dynamic Programming and Optimal Control
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Scalable Techniques from Nonparametric Statistics for Real Time Robot Learning
Applied Intelligence
Reinforcement Learning in the Multi-Robot Domain
Autonomous Robots
Near-Optimal Reinforcement Learning in Polynomial Time
Machine Learning
Noise and the Reality Gap: The Use of Simulation in Evolutionary Robotics
Proceedings of the Third European Conference on Advances in Artificial Life
Reinforcement Learning in Situated Agents: Theoretical and Practical Solutions
EWLR-8 Proceedings of the 8th European Workshop on Learning Robots: Advances in Robot Learning
Direct Policy Search using Paired Statistical Tests
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Approximately Optimal Approximate Reinforcement Learning
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Robot Learning From Demonstration
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Reinforcement Learning for Biped Locomotion
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Learning to Drive a Bicycle Using Reinforcement Learning and Shaping
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Introduction to Stochastic Search and Optimization
Introduction to Stochastic Search and Optimization
Learning in embedded systems
Recent Advances in Hierarchical Reinforcement Learning
Discrete Event Dynamic Systems
R-max - a general polynomial time algorithm for near-optimal reinforcement learning
The Journal of Machine Learning Research
Lyapunov design for safe reinforcement learning
The Journal of Machine Learning Research
The Cross Entropy Method: A Unified Approach To Combinatorial Optimization, Monte-carlo Simulation (Information Science and Statistics)
Apprenticeship learning via inverse reinforcement learning
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
The Journal of Machine Learning Research
Learning from observation using primitives
Learning from observation using primitives
Relating reinforcement learning performance to classification performance
ICML '05 Proceedings of the 22nd international conference on Machine learning
High speed obstacle avoidance using monocular vision and reinforcement learning
ICML '05 Proceedings of the 22nd international conference on Machine learning
Using inaccurate models in reinforcement learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
On the role of tracking in stationary environments
Proceedings of the 24th international conference on Machine learning
Application of reinforcement learning in robot soccer
Engineering Applications of Artificial Intelligence
Learning CPG-based Biped Locomotion with a Policy Gradient Method: Application to a Humanoid Robot
International Journal of Robotics Research
Learning to Control in Operational Space
International Journal of Robotics Research
Trajectory Optimization using Reinforcement Learning for Map Exploration
International Journal of Robotics Research
Free gait generation with reinforcement learning for a six-legged robot
Robotics and Autonomous Systems
Neurocomputing
Operational Space Control: A Theoretical and Empirical Comparison
International Journal of Robotics Research
Space-indexed dynamic programming: learning to follow trajectories
Proceedings of the 25th international conference on Machine learning
Perception and Developmental Learning of Affordances in Autonomous Robots
KI '07 Proceedings of the 30th annual German conference on Advances in Artificial Intelligence
A Reinforcement Learning Technique with an Adaptive Action Generator for a Multi-robot System
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
State-Dependent Exploration for Policy Gradient Methods
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Robot Navigation Based on Fuzzy RL Algorithm
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
A survey of robot learning from demonstration
Robotics and Autonomous Systems
Apprenticeship learning for helicopter control
Communications of the ACM - Barbara Liskov: ACM's A.M. Turing Award Winner
Search-based structured prediction
Machine Learning
Regularization and feature selection in least-squares temporal difference learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Reinforcement learning for robot soccer
Autonomous Robots
Policy Gradient Learning of Cooperative Interaction with a Robot Using User's Biological Signals
Advances in Neuro-Information Processing
Maximum entropy inverse reinforcement learning
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
Automatic gait optimization with Gaussian process regression
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Active learning using mean shift optimization for robot grasping
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
From Motor Learning to Interaction Learning in Robots
From Motor Learning to Interaction Learning in Robots
LQR-trees: Feedback Motion Planning via Sums-of-Squares Verification
International Journal of Robotics Research
Combining active learning and reactive control for robot grasping
Robotics and Autonomous Systems
Reinforcement Learning and Dynamic Programming Using Function Approximators
Reinforcement Learning and Dynamic Programming Using Function Approximators
Learning from Demonstration for Autonomous Navigation in Complex Unstructured Terrain
International Journal of Robotics Research
Learning visual representations for perception-action systems
International Journal of Robotics Research
Learning variable impedance control
International Journal of Robotics Research
Policy search for motor primitives in robotics
Machine Learning
Robot learning from demonstration by constructing skill trees
International Journal of Robotics Research
Learning message-passing inference machines for structured prediction
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Learning reactive and planning rules in a motivationally autonomousanimat
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Learning to pour with a robot arm combining goal and shape learning for dynamic movement primitives
Robotics and Autonomous Systems
Learning Generalizable Control Programs
IEEE Transactions on Autonomous Mental Development
Learning to select and generalize striking movements in robot table tennis
International Journal of Robotics Research
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Reinforcement learning offers to robotics a framework and set of tools for the design of sophisticated and hard-to-engineer behaviors. Conversely, the challenges of robotic problems provide both inspiration, impact, and validation for developments in reinforcement learning. The relationship between disciplines has sufficient promise to be likened to that between physics and mathematics. In this article, we attempt to strengthen the links between the two research communities by providing a survey of work in reinforcement learning for behavior generation in robots. We highlight both key challenges in robot reinforcement learning as well as notable successes. We discuss how contributions tamed the complexity of the domain and study the role of algorithms, representations, and prior knowledge in achieving these successes. As a result, a particular focus of our paper lies on the choice between model-based and model-free as well as between value-function-based and policy-search methods. By analyzing a simple problem in some detail we demonstrate how reinforcement learning approaches may be profitably applied, and we note throughout open questions and the tremendous potential for future research.