Sciweavers

2990 search results - page 549 / 598
» Hidden Markov processes
Sort
View
NIPS
2008
14 years 11 months ago
Biasing Approximate Dynamic Programming with a Lower Discount Factor
Most algorithms for solving Markov decision processes rely on a discount factor, which ensures their convergence. It is generally assumed that using an artificially low discount f...
Marek Petrik, Bruno Scherrer
NIPS
2008
14 years 11 months ago
MDPs with Non-Deterministic Policies
Markov Decision Processes (MDPs) have been extensively studied and used in the context of planning and decision-making, and many methods exist to find the optimal policy for probl...
Mahdi Milani Fard, Joelle Pineau
MOBIMEDIA
2007
14 years 11 months ago
Performance evaluation of IEEE 802.11e based on ON-OFF traffic model
We investigate the performance of the IEEE 802.11e while emphasizing on the end-to-end delay performance. In our MAC delay analysis, we are based on elementary conditional probabi...
Ioannis Papapanagiotou, John S. Vardakas, Georgios...
NIPS
2007
14 years 11 months ago
Optimistic Linear Programming gives Logarithmic Regret for Irreducible MDPs
We present an algorithm called Optimistic Linear Programming (OLP) for learning to optimize average reward in an irreducible but otherwise unknown Markov decision process (MDP). O...
Ambuj Tewari, Peter L. Bartlett
NIPS
2007
14 years 11 months ago
What makes some POMDP problems easy to approximate?
Point-based algorithms have been surprisingly successful in computing approximately optimal solutions for partially observable Markov decision processes (POMDPs) in high dimension...
David Hsu, Wee Sun Lee, Nan Rong