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Introduction

Lecture Notes

Assoc. Prof. Dr. Hürevren Kılıç Computer Engineering Department

Gediz University

Notes are prepared by using book

“Fundamentals of Natural Computing”

written by L.N. de Castro and by using

NACO lecture notes by Thomas Baeck

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Contents

Motivation

NAtural COmputing-NACO Concepts

Branches of NACO and Fields of

Investigation

When to use NACO Approaches ?

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Motivation

Observe, study & understand nature.

Use, re-shape & develop natural resources for

welfare of humanity and ourselves without damaging

and causing any harm on it.

Natural mechanisms: Sources of inspiration or

metaphor for solving complex science & engineering

problems.

Use of computers to simulate & emulate biological

life and processes.

New natural material and means to compute.

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Motivation

Natural Computing: Extracting ideas from nature to

develop computational systems or using natural media

(e.g. molecules) to perform computation (by de Castro)

Development & advancement of NACO benefits to

natural sciences like biology as well (e.g. fields of

Computational Biology and Bioinformatics).

NACO is useful to develop highly abstract models of

nature.

Interaction and similarity between computing and

nature is becoming greater.

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Motivation

Swarm Intelligence

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Motivation

Swarm Intelligence & Self-Organization

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Motivation

Self-Organization

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Motivation

Fractals

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Motivation

Bionics

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Motivation

Bionics

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NACO Concepts

Model: Abstraction of real-world systems or

implementation of a hypothesis in order to investigate

particular questions or to demonstrate particular

features of a system or a hypothesis.

Many details discarded

Simple enough to understand, but

Rich enough to provide behaviors which are

surprising, interesting, useful, significant.

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NACO Concepts

Model is more concerned with quantitatively

reproducing some behavior.

Metaphor: Usually a high level abstraction taken from

a system in order to develop another

Models can

– Assist in prediction

– Simulate behavior of natural systems

– Aid in critical analysis of processes

– Quantitatively describe the system

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NACO Concepts

Simulation: Metaphorical models that “stand for”

something else.

Realization: A literal, material model that implements

certain functions of the original.

Emulation: Imitation or reproduction of a system’s

functions using another system or medium.

NACO does all of above.

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Branches of NAC and Fields of Investigation

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Branches of NAC and Fields of Investigation

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Branches of NAC and Fields of Investigation

A hierarchy:

Subatomic «----» Quantum Computing

Atoms «----» Simulated Annealing

Molecules «----» Molecular Computing

Individual «----» Immunocomputing

Individual «----» Neural Networks

Populations «----» Evolutionary Computation

Populations «----» Swarm Computing

Populations «----» Artificial Life

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When to use NACO approaches ?

Problem to be solved is complex

Impossible to guarantee that a potential solution found is optimal

Problem cannot be suitably modeled

Single solution is not good enough

Biological, physical, chemical systems and processes have to be simulated with realism

Life behaviors and phenomena have to be synthesized in artificial media

Limits of current technology are reached or new computing materials have to be sought

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References

de Castro, L.N. – (2006): Fundamentals of Natural

Computing, Chapman and Hall/CRC.

Baeck, T. – (2014): NACO Lecture Notes Leiden

University Natural Computing Group.