This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
Despite much research that has been done on constraint satisfaction problems (CSP's), the framework is sometimes inflexible and the results are not very satisfactory when app...
We present a technique for computing approximately optimal solutions to stochastic resource allocation problems modeled as Markov decision processes (MDPs). We exploit two key pro...
Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, L...
Given a model of a physical process and a sequence of commands and observations received over time, the task of an autonomous controller is to determine the likely states of the p...
We address the problem of visually detecting causal events and tting them together into a coherent story of the action witnessed by the camera. We show that this can be done by re...