We consider reinforcement learning as solving a Markov decision process with unknown transition distribution. Based on interaction with the environment, an estimate of the transit...
Probabilistic models have been adopted for many computer vision applications, however inference in highdimensional spaces remains problematic. As the statespace of a model grows, ...
Line-art illustrations are effective tools for conveying shapes and shading of complex objects. We present a set of new algorithms to render line-art illustrations of dynamic and s...
We show that global caching can be used with propagation of both satisfiability and unsatisfiability in a sound manner to give an EXPTIME algorithm for checking satisfiability w...
Temporal plans permit significant flexibility in specifying the occurrence time of events. Plan execution can make good use of that flexibility. However, the advantage of executio...
Ioannis Tsamardinos, Nicola Muscettola, Paul H. Mo...