Sciweavers

93 search results - page 11 / 19
» A Novel Prioritization Technique for Solving Markov Decision...
Sort
View
ECAI
1998
Springer
13 years 11 months ago
Optimal Scheduling of Dynamic Progressive Processing
Progressive processing allows a system to satisfy a set of requests under time pressure by limiting the amount of processing allocated to each task based on a predefined hierarchic...
Abdel-Illah Mouaddib, Shlomo Zilberstein
IAT
2005
IEEE
14 years 1 months ago
Decomposing Large-Scale POMDP Via Belief State Analysis
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
Xin Li, William K. Cheung, Jiming Liu
ICML
1999
IEEE
14 years 8 months ago
Least-Squares Temporal Difference Learning
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
Justin A. Boyan
ICPR
2002
IEEE
14 years 10 days ago
Image Flows and One-Liner Graphical Image Representation
In this paper we introduce a novel graphical image representation comprising a single curve—the one-liner. The first step involves the detection and linking of image edges. We ...
Vadim Makhervaks, Gill Barequet, Alfred M. Bruckst...
ATAL
2010
Springer
13 years 8 months ago
Risk-sensitive planning in partially observable environments
Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral in ...
Janusz Marecki, Pradeep Varakantham