252 search results - page 14 / 51 » Learning Partially Observable Action Models: Efficient Algor... |
116
Voted
EWRL
2008
15 years 1 months ago
2008
We consider reinforcement learning in the parameterized setup, where the model is known to belong to a parameterized family of Markov Decision Processes (MDPs). We further impose ...
98
Voted
TSMC
2008
14 years 11 months ago
2008
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
PERCOM
2007
ACM
15 years 11 months ago
2007
ACM
We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...
CORR
2011
Springer
14 years 3 months ago
2011
Springer
We study decision making in environments where the reward is only partially observed, but can be modeled as a function of an action and an observed context. This setting, known as...
110
Voted
ICASSP
2008
IEEE
15 years 6 months ago
2008
IEEE
This paper presents a new framework for accumulating beliefs in spoken dialogue systems. The technique is based on updating a Bayesian Network that represents the underlying state...