We study the maximal reachability probability problem for infinite-state systems featuring both nondeterministic and probabilistic choice. The problem involves the computation of ...
Marta Z. Kwiatkowska, Gethin Norman, Jeremy Sprost...
For probabilistic reasoning, one often needs to sample from a combinatorial space. For example, one may need to sample uniformly from the space of all satisfying assignments. Can ...
Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
We describe a new approximation algorithm for solving partially observable MDPs. Our bounded policy iteration approach searches through the space of bounded-size, stochastic fini...
The availability of indoor positioning renders it possible to deploy location-based services in indoor spaces. Many such services will benefit from the efficient support for k n...