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FLAIRS
2004
13 years 10 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
AIPS
2003
13 years 10 months ago
A Framework for Planning in Continuous-time Stochastic Domains
We propose a framework for policy generation in continuoustime stochastic domains with concurrent actions and events of uncertain duration. We make no assumptions regarding the co...
Håkan L. S. Younes, David J. Musliner, Reid ...
IJCAI
2003
13 years 10 months ago
Generalizing Plans to New Environments in Relational MDPs
A longstanding goal in planning research is the ability to generalize plans developed for some set of environments to a new but similar environment, with minimal or no replanning....
Carlos Guestrin, Daphne Koller, Chris Gearhart, Ne...
UAI
2004
13 years 10 months ago
From Fields to Trees
We present new MCMC algorithms for computing the posterior distributions and expectations of the unknown variables in undirected graphical models with regular structure. For demon...
Firas Hamze, Nando de Freitas
AAAI
2000
13 years 10 months ago
Back to the Future for Consistency-Based Trajectory Tracking
Given a model of a physical process and a sequence of commands and observations received over time, the task of an autonomous controller is to determine the likely states of the p...
James Kurien, P. Pandurang Nayak