In this paper we will look at automated theorem proving for categorial grammar logics. Taking linear logic as a starting point, we will show how proof nets, as an optimal proof theory for the multiplicative fragment of linear logic, can be used to generate proofs for logical statements. We

Abstract. The automated deduction and model checking communities have developed techniques that are impressively e ective when applied to suitable problems. However, these problems seldom coincide exactly with those that arise in formal methods. Using small but realistic examples for illustration

Theory resolution constitutes a set of complete procedures for incorporating theories into a resolution theorem-proving program, thereby making it unnecessary to resolve directly upon axioms of the theory. This can greatly reduce the length of proofs and the size of the search space. Theory resolution effects a beneficial division of labor, improving the performance of the theorem prover and increasing the applicability of the specialized reasoning procedures. Total theory resolution utilizes a decision procedure that is capable of determining unsatisfiability of any set of clauses using predicates in the theory. Partial theory resolution employs a weaker decision procedure that can determine potential unsatisfiability of sets of literals. Applications include the building in of both mathematical and special decision procedures, e.g., for the taxonomic information furnished by a knowledge representation system. Theory resolution is a generalization of numerous previously known resolution refinements. Its power is demonstrated by comparing solutions of "Schubert's Steamroller" challenge problem with and without building in axioms through theory resolution. 1 1

This paper explores the possibility of incorporating conditional proof which is an important deduction strategy in deductive logic into automated deduction to enhance the power of the deduction. It analyses the necessity and feasibility and suggests detailed procedure for the incorporation.

BDDs (binary decision diagrams) are a very succesful tool for handling boolean functions, but one which has not yet attracted the attention of many automated deduction specialists. We give an overview of BDDs from an automated deduction perspective, showing what can be done with them

We survey research in the automation of deductive inference, from its beginnings in the early history of computing to the present day. We identify and describe the major areas of research interest and their applications. The area is characterised by its wide variety of proof methods, forms

. This paper presents three approaches dealing with constraints in automated deduction. Each of them illustrates a different point. The expression of strategies using constraints is shown through the example of a completion process using ordered and basic strategies. The schematization of complex

to partition the search space among cooperating concurrent processes. Motivation The aim of distributed automated deduction is to design distributed strategies that may improve the performance of theorem proving by employing in parallel more than one machine. Higher performance means obtaining proofs

A method is presented for analogical reasoning in Automated Deduction. We focus on the abductive aspects of analogy and give a unified treatment for theorems and non-theorems. Abduction allows to deal with partial analogies thus strongly increasing the application field of the method. It also

SRI International Automated deduction uses computation to perform symbolic logical reasoning. It has been a core technology for program verification from the very beginning. Satisfiability solvers for propositional and first-order logic significantly automate the task of deductive program