A model for reasoning about persistence and causation
Computational Intelligence
Reinforcement learning with hierarchies of machines
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Between MDPs and semi-MDPs: a framework for temporal abstraction in reinforcement learning
Artificial Intelligence
Q-Cut - Dynamic Discovery of Sub-goals in Reinforcement Learning
ECML '02 Proceedings of the 13th European Conference on Machine Learning
Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
PolicyBlocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Discovering Hierarchy in Reinforcement Learning with HEXQ
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Continuous-Time Hierarchical Reinforcement Learning
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Efficient Reinforcement Learning in Factored MDPs
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Hierarchical reinforcement learning with the MAXQ value function decomposition
Journal of Artificial Intelligence Research
Max-norm projections for factored MDPs
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Exploiting structure in policy construction
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
SPUDD: stochastic planning using decision diagrams
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Symbolic generalization for on-line planning
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Causal Graph Based Decomposition of Factored MDPs
The Journal of Machine Learning Research
Decision tree methods for finding reusable MDP homomorphisms
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Episodic task learning in Markov decision processes
Artificial Intelligence Review
Transfer in reinforcement learning via shared features
The Journal of Machine Learning Research
Recognizing internal states of other agents to anticipate and coordinate interactions
EUMAS'11 Proceedings of the 9th European conference on Multi-Agent Systems
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We present Variable Influence Structure Analysis, an algorithm that dynamically performs hierarchical decomposition of factored Markov decision processes. Our algorithm determines causal relationships between state variables and introduces temporally-extended actions that cause the values of state variables to change. Each temporally-extended action corresponds to a subtask that is significantly easier to solve than the overall task. Results from experiments show great promise in scaling to larger tasks.