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AIPS
1994
15 years 20 hour ago
1994
In this work we present an approach to solving time-critical decision-making problems by taking advantage of domain structure to expand the amountof time available for processing ...
AAAI
2000
15 years 1 days ago
2000
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
ICRA
2007
IEEE
15 years 5 months ago
2007
IEEE
Abstract— We provide a method for planning under uncertainty for robotic manipulation by partitioning the configuration space into a set of regions that are closed under complia...
AUTOMATICA
1999
14 years 10 months ago
1999
In this paper, we consider simple classes of nonlinear systems and prove that basic questions related to their stability and controllability are either undecidable or computationa...
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IJRR
2010
14 years 9 months ago
2010
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...