231 search results - page 10 / 47 » Active Learning in Partially Observable Markov Decision Proc... |
SIGECOM
2009
ACM
14 years 3 months ago
2009
ACM
Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent’s decisions by providing limited incentives. In this paper, ...
ICML
2005
IEEE
14 years 9 months ago
2005
IEEE
We study an approach for performing concurrent activities in Markov decision processes (MDPs) based on the coarticulation framework. We assume that the agent has multiple degrees ...
DATE
2008
IEEE
14 years 3 months ago
2008
IEEE
- The effectiveness of stochastic power management relies on the accurate system and workload model and effective policy optimization. Workload modeling is a machine learning proce...
AAAI
2010
13 years 10 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 ...
AAAI
2007
13 years 11 months ago
2007
Planning under uncertainty involves two distinct sources of uncertainty: uncertainty about the effects of actions and uncertainty about the current state of the world. The most wi...