Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling

Authors:
Jan Ramon;Kurt Driessens;Tom Croonenborghs
Affiliations:
K.U. Leuven, Dept. of Computer Science, Celestijnenlaan 200A, B-3001 Leuven,;K.U. Leuven, Dept. of Computer Science, Celestijnenlaan 200A, B-3001 Leuven,;K.U. Leuven, Dept. of Computer Science, Celestijnenlaan 200A, B-3001 Leuven,
Venue:
ECML '07 Proceedings of the 18th European conference on Machine Learning
Year:
2007

Citing 12
Cited 4

Learning in the presence of concept drift and hidden contexts

Machine Learning
Decision Tree Induction Based on Efficient Tree Restructuring

Machine Learning
Blocks World revisited

Artificial Intelligence
Relational reinforcement learning

Machine Learning - Special issue on inducive logic programming
Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner

EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Transfer of Experience Between Reinforcement Learning Environments with Progressive Difficulty

Artificial Intelligence Review
Probabilistic policy reuse in a reinforcement learning agent

AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Transfer via inter-task mappings in policy search reinforcement learning

Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
General game learning using knowledge transfer

IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Utile distinctions for relational reinforcement learning

IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Input generalization in delayed reinforcement learning: an algorithm and performance comparisons

IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
Skill acquisition via transfer learning and advice taking

ECML'06 Proceedings of the 17th European conference on Machine Learning

Evolving Static Representations for Task Transfer

The Journal of Machine Learning Research
Exploration in relational worlds

ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Exploration in relational domains for model-based reinforcement learning

The Journal of Machine Learning Research
Multi model transfer learning with RULES family

MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

We investigate the relation between transfer learning in reinforcement learning with function approximation and supervised learning with concept drift. We present a new incremental relational regression tree algorithm that is capable of dealing with concept drift through tree restructuring and show that it enables a Q-learner to transfer knowledge from one task to another by recycling those parts of the generalized Q-function that still hold interesting information for the new task. We illustrate the performance of the algorithm in several experiments.