Reasoning Theories

Towards an Architecture for Open Mechanized Reasoning Systems
Part of the Applied Logic Series book series (APLS, volume 3)


Our ultimate goal is to provide a framework and a methodology which will allow users, and not only system developers, to construct complex systems by composing existing modules, or to add new modules to existing systems, in a “plug and play” manner. These modules and systems might be based on different logics; have different domain models; use different vocabularies and data structures; use different reasoning strategies; and have different interaction capabilities. This paper, which is a first small step towards our goal, makes two main contributions. First, it proposes a general architecture for a class of reasoning modules and systems called Open Mechanized Reasoning Systems (OMRSs). An OMRS has three components: a reasoning theory component which is the counterpart of the logical notion of formal system, a control component which consists of a set of inference strategies, and an interaction component which provides an OMRS with the capability of interacting with other systems, including OMRSs and human users. Second, it develops the theory underlying the reasoning theory component. This development is illustrated by an analysis of the Boyer-Moore system, NQTHM.


Inference Rule Sequent System Logical Service Reasoning Theory Reasoning Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. A. Avron. Simple consequence relations. LFCS Report, Laboratory for the Foundations of Computer Science, University of Edinburgh, 1987.Google Scholar
  2. R. S. Boyer and J. S. Moore. A Computational Logic. Academic Press, 1979.zbMATHGoogle Scholar
  3. R. S. Boyer and J. S. Moore. Integrating decision procedures into heuristic theorem provers: A case study with linear arithmetic. In Machine Intelligence 11. Oxford University Press, 1988.Google Scholar
  4. F. Giunchiglia and L. Serafini. Multilanguage hierarchical logics (or: how we can do without modal logics). Artificial Intelligence, 65:29–70, 1994.CrossRefzbMATHMathSciNetGoogle Scholar
  5. F. Giunchiglia, P. Pecchiari, and C. L. Talcott. Reasoning theories: Towards an architecture for open mechanized reasoning systems. Technical Report 9409–15, IRST, November 1994. Also appears as Stanford University Computer Science Department Technical Note STAN-CS-94-TN-15.Google Scholar
  6. R. Harper, H. Honsell, and G. Plotkin. A framework for defining logics. In Second Annual Symposium on Logic in Computer Science. IEEE, 1987.Google Scholar
  7. J. Meseguer. General logics. In H.-D. Ebbinghaus et al., editor, Logic Colloquium’87, pages 275–329. North-Holland, 1989.Google Scholar
  8. L. G. Monk. Inference rules using local contexts. Journal of Automated Reasoning, 4:445–462, 1988.CrossRefzbMATHMathSciNetGoogle Scholar
  9. D. S. Scott. Rules and derived rules. In S. Stenlund, editor, Logical Theory and Semantic Analysis, pages 147–161. D. Reidel, 1974.CrossRefGoogle Scholar
  10. I. Sutherland and R. Platek. A plea for logical infrastructure. In TTCP XTP-1 Workshop on Effective Use of Automated Reasoning Technology in System Development, pages 1–3, 1992.Google Scholar

Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  1. 1.IRST and Università di TrentoItaly
  2. 2.IRST and Università di GenovaItaly
  3. 3.Stanford UniversityUSA

Personalised recommendations