In this paper the classical propositional assumption-based model is extended to incorporate probabilities for the assumptions. Then the whole model is placed into the framework of...
We define a logic EpCTL for reasoning about the evolution of probabilistic systems. System states correspond to probability distributions over classical states and the system evo...
Pedro Baltazar, Paulo Mateus, Rajagopal Nagarajan,...
Probabilistic logic programs (PLPs) define a set of probability distribution functions (PDFs) over the set of all Herbrand interpretations of the underlying logical language. When...
Matthias Broecheler, Gerardo I. Simari, V. S. Subr...
This paper addresses the question of how statistical learning algorithms can be integrated into a larger AI system both from a practical engineering perspective and from the persp...
Abstract. A new method is proposed for compiling causal independencies into Markov logic networks (MLNs). An MLN can be viewed as compactly representing a factorization of a joint ...
Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasa...