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FLAIRS
2004
15 years 6 months ago
State Space Reduction For Hierarchical Reinforcement Learning
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
Mehran Asadi, Manfred Huber
ICML
2005
IEEE
16 years 5 months ago
A causal approach to hierarchical decomposition of factored MDPs
We present Variable Influence Structure Analysis, an algorithm that dynamically performs hierarchical decomposition of factored Markov decision processes. Our algorithm determines...
Anders Jonsson, Andrew G. Barto
ICML
2005
IEEE
16 years 5 months ago
Identifying useful subgoals in reinforcement learning by local graph partitioning
We present a new subgoal-based method for automatically creating useful skills in reinforcement learning. Our method identifies subgoals by partitioning local state transition gra...
Özgür Simsek, Alicia P. Wolfe, Andrew G....
DSD
2002
IEEE
86views Hardware» more  DSD 2002»
15 years 9 months ago
Using Formal Tools to Study Complex Circuits Behaviour
We use a formal tool to extract Finite State Machines (FSM) based representations (lists of states and transitions) of sequential circuits described by flip-flops and gates. The...
Paul Amblard, Fabienne Lagnier, Michel Lévy
NAACL
2003
15 years 6 months ago
Towards Emotion Prediction in Spoken Tutoring Dialogues
Human tutors detect and respond to student emotional states, but current machine tutors do not. Our preliminary machine learning experiments involving transcription, emotion annot...
Diane J. Litman, Katherine Forbes, Scott Silliman