Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
An important branch of investigation in the field agents has been the definition of high level languages for representing effects of actions, the programs written in such languages...
We describe a novel approach to quadrature for ratios of probabilistic integrals, such as are used to compute posterior probabilities. This approach offers performance superior t...
Michael A. Osborne, Roman Garnett, Stephen J. Robe...
In joint work with Peter O’Hearn and others, based on early ideas of Burstall, we have developed an extension of Hoare logic that permits reasoning about low-level imperative pr...
Soundness proofs of program logics such as Hoare logics and type systems are often made easier by decorating the operational semantics with information that is useful in the proof...