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FOLASP: FO(.) as Input Language for Answer Ser Solvers
We present experimental results to show that the resulting combination of our translation with an off-the-shelf ASP solver is competitive with the IDP system as a way of solving problems formulated in FO(.).
Planning with Learned Binarized Neural Networks Benchmarks for MaxSAT Evaluation 2021
This document provides a brief introduction to learned automated planning problem where the state transition function is in the form of a binarized neural network (BNN), presents a general MaxSAT encoding for this problem, and describes the four domains, namely: Navigation, Inventory Control, System Administrator and Cellda, that are submitted as benchmarks for MaxSAT Evaluation 2021.
A MIP Backend for the IDP System
The IDP knowledge base system currently uses MiniSAT(ID) as its backend Constraint Programming (CP) solver.
BreakID: Static Symmetry Breaking for ASP (System Description)
Symmetry breaking has been proven to be an efficient preprocessing technique for satisfiability solving (SAT).
Implementing a Relevance Tracker Module
PC(ID) extends propositional logic with inductive definitions: rule sets under the well-founded semantics.
