This paper describes a deterministic method for generating natural language suited to being part of a machine translation system with meaning representations as the level for language transfer. Starting from Davidsonian/Penman meaning representations, syntactic trees are built following the Penn Parsed Corpus of Modern British English, from which the yield (i.e., the words) can be taken. The no...

Currently, the most effective complete SAT solvers are based on the DPLL algorithm augmented by clause learning. These solvers can handle many real-world problems from application areas like verification, diagnosis, planning, and design. Without clause learning, however, DPLL loses most of its effectiveness on real world problems. Recently there has been some work on obtaining a deeper understa...

Conjunctive Normal Form (CNF) Boolean formulas generated from resolution or solution enumeration often have much redundancy. It is desirable to have an efficient algorithm to simplify and compact such CNF formulas on the fly. Given a clause in a CNF formula, if a subset of its literals constitutes another clause in the formula, then the first clause is said to be subsumed by the second clause. ...

In this paper we consider first-order logic theorem proving and model building via approximation and instantiation. Given a clause set we propose its approximation into a simplified clause set where satisfiability is decidable. The approximation extends the signature and preserves unsatisfiability: if the simplified clause set is satisfiable in some model, so is the original clause set in the s...