Controlled Mobile Radiation Detection Under Stochastic Uncertainty
نویسندگان
چکیده
منابع مشابه
Controlled Kicking under Uncertainty
In RoboCup, robots must make quick decisions under uncertainty. To this end, this paper introduces a new approach to enable humanoid soccer robots to execute kicks quickly and ensure that they move the ball down field. This paper presents a kick engine capable of kicking at a variety of distances and angles and then describes a novel kick decision method for selecting from among a large set of ...
متن کاملPlanning Under Uncertainty via Stochastic Statisfiability
A probabilistic propositional planning problem can be solved by converting it to a stochastic satisfiability problem and solving that problem instead. I have developed three planners that use this approach: MAXPLAN~ G-MAXPLAN~ and ZANDER. MAXPLAN~ which assumes complete unobservability, converts a dynamic belief network representation of the planning problem to an instance of a stochastic satis...
متن کاملStochastic programming approach to optimization under uncertainty
In this paper we discuss computational complexity and risk averse approaches to two and multistage stochastic programming problems. We argue that two stage (say linear) stochastic programming problems can be solved with a reasonable accuracy by Monte Carlo sampling techniques while there are indications that complexity of multistage programs grows fast with increase of the number of stages. We ...
متن کاملDesign under Uncertainty Employing Stochastic Expansion Methods
Nonintrusive polynomial chaos expansion (PCE) and stochastic collocation (SC) methods are attractive techniques for uncertainty quantification due to their fast convergence properties and ability to produce functional representations of stochastic variability. PCE estimates coefficients for known orthogonal polynomial basis functions based on a set of response function evaluations, using sampli...
متن کاملContingent Planning Under Uncertainty via Stochastic Satisfiability
We describe a new planning technique that efficiently solves probabilistic propositional contingent planning problems by converting them into instances of stochastic satisfiability (SSat) and solving these problems instead. We make fundamental contributions in two areas: the solution of SSat problems and the solution of stochastic planning problems. This is the first work extending the planning...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Control Systems Letters
سال: 2017
ISSN: 2475-1456
DOI: 10.1109/lcsys.2017.2712603