Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...
This paper proposes a logic for causal based on event trees. Event trees provide a natural and familiar framework for probability and decision theory, but they lack the modularity...
In this paper, the feasibility of using finite totally ordered probability models under Aleliunas’s Theory of Probabilistic Logic [Aleliunas, 1988] is investigated. The general...
Advancing the synthesis of Eastern mind science with Western physical science will require a robust and easy-to-traverse bridge between the atypical apprehensions within meditation...
Novelty detection is concerned with identifying abnormal system behaviours and abrupt changes from one regime to another. This paper proposes an on-line (causal) novelty detection...