43 search results - page 7 / 9 » Belief Selection in Point-Based Planning Algorithms for POMD... |
NIPS
2007
14 years 11 months ago
2007
Planning in partially observable environments remains a challenging problem, despite significant recent advances in offline approximation techniques. A few online methods have a...
ECML
2005
Springer
15 years 3 months ago
2005
Springer
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...
AAAI
2010
14 years 11 months ago
2010
Trial-based approaches offer an efficient way to solve singleagent MDPs and POMDPs. These approaches allow agents to focus their computations on regions of the environment they en...
ICRA
2008
IEEE
15 years 4 months ago
2008
IEEE
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
CIMCA
2008
IEEE
15 years 4 months ago
2008
IEEE
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...