We propose an approach for the integration of abduction and induction in Logic Programming. In particular, we show how it is possible to learn an abductive logic program starting f...
Probabilistic Horn abduction is a simple framework to combine probabilistic and logical reasoning into a coherent practical framework. The numbers can be consistently interpreted ...
We report on the design of a prototyping component for the theorem prover Isabelle/HOL. Specifications consisting of datatypes, recursive functions and inductive definitions are co...
The Connectionist Inductive Learning and Logic Programming System, C-IL 2 P, integrates the symbolic and connectionist paradigms of Artificial Intelligence through neural networks...
1 In [20], a new Hybrid Probabilistic Logic Programs framework is proposed, and a new semantics is developed to enable encoding and reasoning about real-world applications. In this...