intro to natural computing
description
Transcript of intro to natural computing
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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.