The current best conformant probabilistic planners encode the problem as a bounded length CSP or SAT problem. While these approaches can find optimal solutions for given plan leng...
Daniel Bryce, Subbarao Kambhampati, David E. Smith
The current best conformant probabilistic planners encode the problem as a bounded length CSP or SAT problem. While these approaches can find optimal solutions for given plan leng...
Daniel Bryce, Subbarao Kambhampati, David E. Smith
The sparse grid discretization technique enables a compressed representation of higher-dimensional functions. In its original form, it relies heavily on recursion and complex data...
Alin Florindor Murarasu, Josef Weidendorfer, Gerri...
Background: The question of how a circle or line segment becomes covered when random arcs are marked off has arisen repeatedly in bioinformatics. The number of uncovered gaps is o...
John Moriarty, Julian R. Marchesi, Anthony Metcalf...
A weakness of classical Markov decision processes (MDPs) is that they scale very poorly due to the flat state-space representation. Factored MDPs address this representational pro...