PITA

swMATH6950MaRDI QIDQ19014

No author found.

Described by source

• The PITA system: Tabling and answer subsumption for reasoning under uncertainty
• Well–definedness and efficient inference for probabilistic logic programming under the distribution semantics

Related Items (22)

Efficient Knowledge Compilation Beyond Weighted Model Counting ⋮ The distribution semantics for normal programs with function symbols ⋮ \(T_{\mathcal{P}}\)-compilation for inference in probabilistic logic programs ⋮ Constraint-Based Inference in Probabilistic Logic Programs ⋮ A functional account of probabilistic programming with possible worlds. Declarative pearl ⋮ Unnamed Item ⋮ Causal inference in cplint ⋮ Viterbi training in PRISM ⋮ Structure learning of probabilistic logic programs by searching the clause space ⋮ Probabilistic (logic) programming concepts ⋮ Bandit-based Monte-Carlo structure learning of probabilistic logic programs ⋮ Lifted discriminative learning of probabilistic logic programs ⋮ An OpenCL implementation of a forward sampling algorithm for CP-logic ⋮ Constructing generative logical models for optimisation problems using domain knowledge ⋮ Learning Effect Axioms via Probabilistic Logic Programming ⋮ Unnamed Item ⋮ MAP Inference for Probabilistic Logic Programming ⋮ Probabilistic DL Reasoning with Pinpointing Formulas: A Prolog-based Approach ⋮ Probabilistic abstract argumentation frameworks, a possible world view ⋮ Learning hierarchical probabilistic logic programs ⋮ Tabling and answer subsumption for reasoning on logic programs with annotated disjunctions ⋮ Unnamed Item

This page was built for software: PITA