Learning general truths from the observation of simple domains and, further, learning how to use this knowledge are essential capabilities for any intelligent agent to understand ...
Paulo Santos, Derek R. Magee, Anthony G. Cohn, Dav...
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
In this paper, we describe a receding horizon scheme that satisfies a class of linear temporal logic specifications sufficient to describe a wide range of properties including saf...
Tichakorn Wongpiromsarn, Ufuk Topcu, Richard M. Mu...
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
Temporal logic can be used as a programming language. If temporal formulae are represented in the form of an implication where the antecedent refers to the past, and the consequen...
Howard Barringer, Michael Fisher, Dov M. Gabbay, A...