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RC
2007
78views more  RC 2007»
15 years 3 months ago
Monte-Carlo-Type Techniques for Processing Interval Uncertainty, and Their Potential Engineering Applications
Abstract. In engineering applications, we need to make decisions under uncertainty. Traditionally, in engineering, statistical methods are used, methods assuming that we know the p...
Vladik Kreinovich, Jan Beck, Carlos Ferregut, Arac...
TSP
2008
151views more  TSP 2008»
15 years 3 months ago
Convergence Analysis of Reweighted Sum-Product Algorithms
Markov random fields are designed to represent structured dependencies among large collections of random variables, and are well-suited to capture the structure of real-world sign...
Tanya Roosta, Martin J. Wainwright, Shankar S. Sas...
UAI
2004
15 years 5 months ago
Solving Factored MDPs with Continuous and Discrete Variables
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...
AIPS
2007
15 years 6 months ago
Learning to Plan Using Harmonic Analysis of Diffusion Models
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...
ERCIM
2008
78views more  ERCIM 2008»
15 years 4 months ago
Test Coverage Analysis and Preservation for Requirements-Based Testing
The testing process for safety-critical systems is usually evaluated with code coverage criteria such as MC/DC (Modified Condition/Decision Coverage) defined in the standard DO-17...
Raimund Kirner, Susanne Kandl