Models of Massive Parallelism

1. Front Matter

   Pages I-XIV

   PDF

2. Turing Computability and Complexity

   • Max Garzon

   Pages 1-15

3. Cellular Automata

   • Max Garzon

   Pages 17-38

4. Linear Cellular Automata

   • Max Garzon

   Pages 39-62

5. Semi-totalistic Automata

   • Max Garzon

   Pages 63-78

6. Decision Problems

   • Max Garzon

   Pages 79-96

7. Neural and Random Boolean Networks

   • Max Garzon

   Pages 97-116

8. General Properties

   • Max Garzon

   Pages 117-139

9. Classification

   • Max Garzon

   Pages 141-166

10. Asymptotic Behavior

    • Max Garzon

    Pages 167-198

11. Some Inverse Problems

    • Old folk

    Pages 199-229

12. Real Computation

    • Charles P. Baudelaire

    Pages 231-254

13. A Bibliography of Applications

    • Max Garzon

    Pages 255-262

14. Back Matter

    Pages 263-274

    PDF

Locality is a fundamental restriction in nature. On the other hand, adaptive complex systems, life in particular, exhibit a sense of permanence and time­ lessness amidst relentless constant changes in surrounding environments that make the global properties of the physical world the most important problems in understanding their nature and structure. Thus, much of the differential and integral Calculus deals with the problem of passing from local information (as expressed, for example, by a differential equation, or the contour of a region) to global features of a system's behavior (an equation of growth, or an area). Fundamental laws in the exact sciences seek to express the observable global behavior of physical objects through equations about local interaction of their components, on the assumption that the continuum is the most accurate model of physical reality. Paradoxically, much of modern physics calls for a fundamen­ tal discrete component in our understanding of the physical world. Useful computational models must be eventually constructed in hardware, and as such can only be based on local interaction of simple processing elements.

• (diskrete) neural networks
• algorithmic complexity
• algorithmische Komplexität
• algorithms
• automata
• cellular automata
• complexity
• computational complexity
• dynamical systems
• dynamische Systeme
• network
• neural networks
• neutral networks
• topology of compact spaces
• zellulare Automaten

• Department of Mathematical Sciences, The University of Memphis, Memphis, USA

  Max Garzon

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