Reinforcement learning with replacing eligibility traces
Machine Learning - Special issue on reinforcement learning
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Transfer of Experience Between Reinforcement Learning Environments with Progressive Difficulty
Artificial Intelligence Review
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Value-function-based transfer for reinforcement learning using structure mapping
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Using Homomorphisms to transfer options across continuous reinforcement learning domains
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Skill acquisition via transfer learning and advice taking
ECML'06 Proceedings of the 17th European conference on Machine Learning
Autonomous transfer for reinforcement learning
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Graph Laplacian based transfer learning in reinforcement learning
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Spatial Abstraction: Aspectualization, Coarsening, and Conceptual Classification
Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space
Learning to Recognize Activities from the Wrong View Point
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
On universal transfer learning
Theoretical Computer Science
Autonomous inter-task transfer in reinforcement learning domains
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Transfer Learning for Reinforcement Learning Domains: A Survey
The Journal of Machine Learning Research
Skill combination for reinforcement learning
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Generalization and transfer learning in noise-affected robot navigation tasks
EPIA'07 Proceedings of the aritficial intelligence 13th Portuguese conference on Progress in artificial intelligence
Relational macros for transfer in reinforcement learning
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Transfer learning through indirect encoding
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Combining manual feedback with subsequent MDP reward signals for reinforcement learning
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Evolving Static Representations for Task Transfer
The Journal of Machine Learning Research
Structural knowledge transfer by spatial abstraction for reinforcement learning agents
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Video summarization via transferrable structured learning
Proceedings of the 20th international conference on World wide web
Integrating reinforcement learning with human demonstrations of varying ability
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Supervised learning with minimal effort
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Abstraction and generalization in reinforcement learning: a summary and framework
ALA'09 Proceedings of the Second international conference on Adaptive and Learning Agents
Which should we try first? ranking information resources through query classification
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
ACM SIGKDD Explorations Newsletter
Reinforcement learning transfer using a sparse coded inter-task mapping
EUMAS'11 Proceedings of the 9th European conference on Multi-Agent Systems
Transferring task models in Reinforcement Learning agents
Neurocomputing
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
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A typical goal for transfer learning algorithms is to utilize knowledge gained in a source task to learn a target task faster. Recently introduced transfer methods in reinforcement learning settings have shown considerable promise, but they typically transfer between pairs of very similar tasks. This work introduces Rule Transfer, a transfer algorithm that first learns rules to summarize a source task policy and then leverages those rules to learn faster in a target task. This paper demonstrates that Rule Transfer can effectively speed up learning in Keepaway, a benchmark RL problem in the robot soccer domain, based on experience from source tasks in the gridworld domain. We empirically show, through the use of three distinct transfer metrics, that Rule Transfer is effective across these domains.