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» Incremental Deterministic Planning
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ICML
2010
IEEE
13 years 5 months ago
Constructing States for Reinforcement Learning
POMDPs are the models of choice for reinforcement learning (RL) tasks where the environment cannot be observed directly. In many applications we need to learn the POMDP structure ...
M. M. Hassan Mahmud
IROS
2009
IEEE
123views Robotics» more  IROS 2009»
14 years 2 months ago
Planning-based prediction for pedestrians
— We present a novel approach for determining robot movements that efficiently accomplish the robot’s tasks while not hindering the movements of people within the environment....
Brian Ziebart, Nathan D. Ratliff, Garratt Gallaghe...
ECML
2005
Springer
14 years 1 months ago
Active Learning in Partially Observable Markov Decision Processes
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Robin Jaulmes, Joelle Pineau, Doina Precup
ICSR
2009
Springer
14 years 5 days ago
Consistency Checking for Component Reuse in Open Systems
Large scale Open Systems are built from reusable components in such a way that enhanced system functionality can be deployed, quickly and effectively, simply by plugging in a few n...
Peter Henderson, Matthew J. Henderson
WETICE
1996
IEEE
13 years 11 months ago
Independent validation of specifications: a coordination headache
Large, complex projects face significant barriers to coordination and communication due to continuous, rapid changes during a project's lifecycle. Such changes must be tracke...
Steve M. Easterbrook, John R. Callahan