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Self-organization in computational systems: Advance of a new computational paradigm?

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Parallelism, Learning, Evolution (WOPPLOT 1989)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 565))

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Abstract

To summarize, we should like to give some (doubtful?) answers to some (doubtful?) questions:

What are Neural Networks?

  • the omnipotent medicine for solving AI-problems or

  • just a new paradigm for information processing

What is evolution?

  • the omnipotent medicine for curing neural network shortcomings or diseases or

  • just a new paradigm for tuning system parameters according to some optimization function or

  • discovering new mechanisms or “frames of effect”, i.e. a set of meta-rules for meta-programming, hoping that the cardinality of that set of meta-rules is less than the cardinality of the set of common program writing rules.

What is the governing principle behind evolution?

  • selection of the fittest in a hostile environment or

  • an optimistic force driven from within living beings (“new biology”; cf. MÜhlenbein's contribution to this volume).

What is self-organization?

  • just a new gap-filler for unexplicable phenomena in systems.

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J. D. Becker I. Eisele F. W. Mündemann

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© 1991 Springer-Verlag Berlin Heidelberg

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Mündemann, F.W. (1991). Self-organization in computational systems: Advance of a new computational paradigm?. In: Becker, J.D., Eisele, I., Mündemann, F.W. (eds) Parallelism, Learning, Evolution. WOPPLOT 1989. Lecture Notes in Computer Science, vol 565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55027-5_18

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  • DOI: https://doi.org/10.1007/3-540-55027-5_18

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