research-article

Dynamic Reasoning Systems

Author:

Daniel G. SchwartzAuthors Info & Claims

ACM Transactions on Computational Logic (TOCL), Volume 16, Issue 4

Article No.: 32, Pages 1 - 42

https://doi.org/10.1145/2798727

Published: 14 November 2015 Publication History

Abstract

A dynamic reasoning system (DRS) is an adaptation of a conventional formal logical system that explicitly portrays reasoning as a temporal activity, with each extralogical input to the system and each inference rule application being viewed as occurring at a distinct timestep. Every DRS incorporates some well-defined logic together with a controller that serves to guide the reasoning process in response to user inputs. Logics are generic, whereas controllers are application specific. Every controller does, nonetheless, provide an algorithm for nonmonotonic belief revision. The general notion of a DRS comprises a framework within which one can formulate the logic and algorithms for a given application and prove that the algorithms are correct, that is, that they serve to (1) derive all salient information and (2) preserve the consistency of the belief set. This article illustrates the idea with ordinary first-order predicate calculus, suitably modified for the present purpose, and two examples. The latter example revisits some classic nonmonotonic reasoning puzzles (Opus the Penguin, Nixon Diamond) and shows how these can be resolved in the context of a DRS, using an expanded version of first-order logic that incorporates typed predicate symbols. All concepts are rigorously defined and effectively computable, thereby providing the foundation for a future software implementation.

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Cited By

Shu XAraujo FSchales DStoecklin MJang JHuang HRao JLie DMannan MBackes MWang X(2018)Threat Intelligence ComputingProceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security10.1145/3243734.3243829(1883-1898)Online publication date: 15-Oct-2018
https://dl.acm.org/doi/10.1145/3243734.3243829

Index Terms

Dynamic Reasoning Systems
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
  2. Symbolic and algebraic manipulation
    1. Symbolic and algebraic algorithms
      1. Theorem proving algorithms

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cover image ACM Transactions on Computational Logic

ACM Transactions on Computational Logic Volume 16, Issue 4

November 2015

273 pages

ISSN:1529-3785

EISSN:1557-945X

DOI:10.1145/2802139

Editor:
Orna Kupferman
School of Computer Science and Engineering, Hebrew University, Israel

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Copyright © 2015 ACM.

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Publication History

Published: 14 November 2015

Accepted: 01 June 2015

Revised: 01 June 2015

Received: 01 July 2013

Published in TOCL Volume 16, Issue 4

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Cited By

Shu XAraujo FSchales DStoecklin MJang JHuang HRao JLie DMannan MBackes MWang X(2018)Threat Intelligence ComputingProceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security10.1145/3243734.3243829(1883-1898)Online publication date: 15-Oct-2018
https://dl.acm.org/doi/10.1145/3243734.3243829

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