Formal Modeling of Connectionism using Concurrency Theory, an Approach Based on Automata and Model Checking

Su, Li and Bowman, H. and Wyble, Brad (2006) Formal Modeling of Connectionism using Concurrency Theory, an Approach Based on Automata and Model Checking. Technical report. UKC (Full text available)

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Abstract

This paper illustrates a framework for applying formal methods techniques, which are symbolic in nature, to specifying and verifying neural networks, which are sub-symbolic in nature. The paper describes a communicating automata [Bowman & Gomez, 2006] model of neural networks. We also implement the model using timed automata [Alur & Dill, 1994] and then undertake a verification of these models using the model checker Uppaal [Pettersson, 2000] in order to evaluate the performance of learning algorithms. This paper also presents discussion of a number of broad issues concerning cognitive neuroscience and the debate as to whether symbolic processing or connectionism is a suitable representation of cognitive systems. Additionally, the issue of integrating symbolic techniques, such as formal methods, with complex neural networks is discussed. We then argue that symbolic verifications may give theoretically well-founded ways to evaluate and justify neural learning systems in the field of both theoretical research and real world applications.

Item Type: Monograph (Technical report)
Uncontrolled keywords: formal methods, communicating automata, timed automata, model checking, symbolic, sub-symbolic, neural networks, cognition, learning
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Applied and Interdisciplinary Informatics Group
Faculties > Science Technology and Medical Studies > School of Computing > Computational Intelligence Group
Faculties > Science Technology and Medical Studies > School of Computing > Theoretical Computing Group
Depositing User: Mark Wheadon
Date Deposited: 24 Nov 2008 18:04
Last Modified: 20 Apr 2012 11:36
Resource URI: http://kar.kent.ac.uk/id/eprint/14514 (The current URI for this page, for reference purposes)
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