98 search results - page 4 / 20 » Using Rewards for Belief State Updates in Partially Observab... |
CSL
2007
Springer
13 years 7 months ago
2007
Springer
In a spoken dialog system, determining which action a machine should take in a given situation is a difficult problem because automatic speech recognition is unreliable and hence ...
CSL
2010
Springer
13 years 7 months ago
2010
Springer
This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on...
AAAI
2010
13 years 9 months ago
2010
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...
IROS
2009
IEEE
14 years 2 months ago
2009
IEEE
— Partially Observable Markov Decision Processes (POMDPs) provide a rich mathematical model to handle realworld sequential decision processes but require a known model to be solv...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...