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Propositional Automata and Cell Automata: Representational Frameworks for Discrete Dynamic Systems

  • Eric Schkufza
  • Nathaniel Love
  • Michael Genesereth
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5360)

Abstract

This paper describes and compares two simple, powerful models for formalizing the behavior of discrete dynamic systems: Propositional and Cell Automata. Propositional Automata encode state in terms of boolean propositions, and behavior in terms of boolean gates and latches. Cell Automata generalize the propositional model by encoding state in terms of multi-valued cells, and behavior in terms of comparators and selectors that respond to cell values. While the models are equally expressive, Cell Automata are computationally more efficient than Propositional Automata. Additionally, arbitrary Propositional Automata can be converted to optimal Cell Automata with identical behavioral properties, and Cell Automata can be encoded as a Propositional Automata with only logarithmic increase in size.

Keywords

Connectivity Function Discrete Dynamic System Business Process Execution Language Abstract State Machine Base Proposition 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Eric Schkufza
    • 1
  • Nathaniel Love
    • 1
  • Michael Genesereth
    • 1
  1. 1.Stanford UniversityUSA

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