We use reconfigurable hardware to construct a high throughput Bayesian computing machine (BCM) capable of evaluating probabilistic networks with arbitrary DAG (directed acyclic gr...
Abstract. We show how a program analysis technique originally developed for C-like pointer structures can be adapted to analyse the hierarchical structure of processes in the ambie...
We introduce graph reduction technology that implements functional languages with control, such as Scheme with call/cc, where continuations can be manipulated explicitly as values,...
The paper provides a uniform representation of abductive reasoning in the logical framework of causal inference relations. The representation covers in a single framework not only...
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...