Reinforcement learning with hierarchies of machines
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Multi-time models for temporally abstract planning
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Bucket elimination: a unifying framework for reasoning
Artificial Intelligence
Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Coordinated Reinforcement Learning
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
State abstraction for programmable reinforcement learning agents
Eighteenth national conference on Artificial intelligence
Programmable reinforcement learning agents
Programmable reinforcement learning agents
Hierarchical reinforcement learning with the MAXQ value function decomposition
Journal of Artificial Intelligence Research
Generalizing plans to new environments in relational MDPs
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Adaptive Multi-Agent Programming in GTGolog
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Extending the Strada Framework to Design an AI for ORTS
ICEC '09 Proceedings of the 8th International Conference on Entertainment Computing
Dynamic scheduling of maintenance tasks in the petroleum industry: A reinforcement approach
Engineering Applications of Artificial Intelligence
Concurrent hierarchical reinforcement learning
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 4
Discover relevant environment feature using concurrent reinforcement learning
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Behavior bounding: an efficient method for high-level behavior comparison
Journal of Artificial Intelligence Research
Effective control knowledge transfer through learning skill and representation hierarchies
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Adaptive multi-agent programming in GTGolog
KI'06 Proceedings of the 29th annual German conference on Artificial intelligence
Improving the performance of complex agent plans through reinforcement learning
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Time-based reward shaping in real-time strategy games
ADMI'10 Proceedings of the 6th international conference on Agents and data mining interaction
LearnPNP: a tool for learning agent behaviors
RoboCup 2010
Coordination guided reinforcement learning
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
| Hi-index | 0.00 |
We consider applying hierarchical reinforcement learning techniques to problems in which an agent has several effectors to control simultaneously. We argue that the kind of prior knowledge one typically has about such problems is best expressed using a multithreaded partial program, and present concurrent ALisp, a language for specifying such partial programs. We describe algorithms for learning and acting with concurrent ALisp that can be efficient even when there are exponentially many joint choices at each decision point. Finally, we show results of applying these methods to a complex computer game domain.