ICRA
2010
IEEE
13 years 3 months ago
2010
IEEE
— Partially Observable Markov Decision Processes (POMDPs) offer a powerful mathematical framework for making optimal action choices in noisy and/or uncertain environments, in par...
AROBOTS
2008
13 years 3 months ago
2008
Abstract Many elderly and physically impaired people experience difficulties when maneuvering a powered wheelchair. In order to provide improved maneuvering, powered wheelchairs ha...
JAIR
2000
13 years 4 months ago
2000
Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in whic...
ARTMED
2000
13 years 4 months ago
2000
Diagnosis of a disease and its treatment are not separate, one-shot activities. Instead, they are very often dependent and interleaved over time. This is mostly due to uncertainty...
JAIR
2008
13 years 5 months ago
2008
Partially Observable Markov Decision Processes (POMDPs) provide a rich framework for sequential decision-making under uncertainty in stochastic domains. However, solving a POMDP i...
ATAL
2010
Springer
13 years 6 months ago
2010
Springer
In this paper, we study a particular subclass of partially observable models, called quasi-deterministic partially observable Markov decision processes (QDET-POMDPs), characterize...
NIPS
2004
13 years 6 months ago
2004
Existing algorithms for discrete partially observable Markov decision processes can at best solve problems of a few thousand states due to two important sources of intractability:...
AIPS
2003
13 years 6 months ago
2003
We develop a hierarchical approach to planning for partially observable Markov decision processes (POMDPs) in which a policy is represented as a hierarchical finite-state control...
AAAI
2004
13 years 6 months ago
2004
The search for finite-state controllers for partially observable Markov decision processes (POMDPs) is often based on approaches like gradient ascent, attractive because of their ...
ICMLA
2008
13 years 6 months ago
2008
High dimensionality of belief space in Partially Observable Markov Decision Processes (POMDPs) is one of the major causes that severely restricts the applicability of this model. ...