We study the problem of probabilistic deduction with conditional constraints over basic events. We show that globallycomplete probabilistic deduction with conditional constraints ...
There has been a lot of interest of late for programming languages that incorporate features from dependent type systems and proof assistants in order to capture in the types impo...
iLTL is a probabilistic temporal logic that can specify properties of multiple discrete time Markov chains (DTMCs). In this paper, we describe two related tools: MarkovEstimator a...
There are a lot of industrial applications that can be solved competitively by hard computing, while still requiring the tolerance for imprecision and uncertainty that can be explo...
A highly desired part of the synthetic biology toolbox is an embedded chemical microcontroller, capable of autonomously following a logic program specified by a set of instructions...
David Soloveichik, Matthew Cook, Erik Winfree, Jeh...