Quantitative results concerning the utility of explanation-based learning
Artificial Intelligence
HTN planning: complexity and expressivity
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
A Heuristic Approach to the Discovery of Macro-Operators
Machine Learning
Chunking in Soar: The Anatomy of a General Learning Mechanism
Machine Learning
ECML '00 Proceedings of the 11th European Conference on Machine Learning
Learning Goal-Decomposition Rules using Exercises
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
ICDL '02 Proceedings of the 2nd International Conference on Development and Learning
An Architecture for Persistent Reactive Behavior
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Teleo-reactive programs for agent control
Journal of Artificial Intelligence Research
Learning to improve both efficiency and quality of planning
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Acquiring recursive concepts with explanation-based learning
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
The effect of rule use on the utility of explanation-based learning
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
SteppingStone: an empirical and analytical evaluation
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
Learning Recursive Control Programs from Problem Solving
The Journal of Machine Learning Research
POIROT: integrated learning of web service procedures
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Inductive generalization of analytically learned goal hierarchies
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Using a teleo-reactive approach in building self-managing systems
International Journal of Autonomous and Adaptive Communications Systems
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In this paper, we focus on the problem of learning reactive skills for use by physical agents. We propose a new representation for such procedures, teleoreactive logic programs, along with an interpreter that utilizes them to achieve goals. After this, we describe a learning method that acquires these structures in a cumulative manner through problem solving. We report experiments in three domains that involve multiple levels of skilled behavior. We also review related work and discuss directions for future research.