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2005: A Matlab Tour on Artificial Immune Systems

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Leandro de Castro
Leandro de Castro

BIC 2005 (Biologically Inspired Computing Conference), Johor, Malaysia

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A Matlab Tour on Some AIS Algorithms BIC 2005: International Symposium on Bio-Inspired Computing Johor, MY, 10 th September 2005 Dr. Leandro Nunes de Castro [email_address] http://lsin.unisantos.b/lnunes Catholic University of Santos - UniSantos/Brazil
[object Object],[object Object],[object Object],[object Object],[object Object],Outline
CLONALG A Clonal Selection Algorithm
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],CLONALG
Clonal Selection Principle
Continuous Learning
Affinity Maturation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Hypermutation  Editing
CLONALG: Block Diagram
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],CLONALG: Algorithm
Test Problem I ,[object Object],[object Object]
[object Object],CLONALG - Performance I 00 generations 10 generations 20 generations 50 generations 75 generations 100 generations 150 generations 200 generations 250 generations
[object Object],[object Object],Test Problem II 200 individuals randomly distributed
[object Object],[object Object],CLONALG - Performance II GA CLONALG
[object Object],[object Object],Test Problem III Cities Optimal Path (48872 um) 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 7 1 8 14 2 15 3 4 11 12 13 17 23 27 30 26 19 21 24 29 28 25 22 20 18 16 6 9 10 5
[object Object],CLONALG - Performance III
CLONALG: Discussion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
aiNet An Artificial Immune Network
Immune Network Theory
aiNet: Basic Principles (I) ,[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],aiNet: Basic Principles (II)
aiNet: Training Algorithm ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],aiNet: Arithmetic
Test Problem I ,[object Object],0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 x y Training Patterns
aiNet - Performance I Minimal Spanning Tree 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Number of Clusters (Valleys) 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14
0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Final Network Structure aiNet - Performance I
[object Object],Test Problem II -2 -1 0 1 2 -2 0 2 4 -1.5 -1 -0.5 0 0.5 1 1.5
Number of Clusters (Valleys) Minimal Spanning Tree aiNet - Performance II 1 0 5 10 15 20 25 30 35 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
-1 -0.5 0 0.5 1 -1 0 1 2 3 -1 -0.5 0 0.5 1 1.5 Final Network Structure aiNet - Performance II
aiNet: Discussion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
ABNET An Antibody Network
ABNET ,[object Object],[object Object],[object Object]
ABNET: Basic Functioning (I)
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],ABNET: Basic Functioning (I)
ABNET: Growing
ABNET: Pruning
ABNET: Weight Update
ABNET - Performance 2) Cross-reactivity (generalization) (a)   13.75% Noise tolerance: (b)   13.75%
ABNET: Discussion ,[object Object],[object Object],[object Object],[object Object]
Opt-aiNet An Optimization version of aiNet
Introduction ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Immune Networks ,[object Object]
opt-aiNet ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Related Strategies ,[object Object],[object Object],[object Object],[object Object]
Simulation Results (I) ,[object Object]
Simulation Results (II) ,[object Object]
Simulation Results (III) ,[object Object]
Opt-aiNet: Discussion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Final Comments ,[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],Final Comments
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Final Comments
Final Comments ,[object Object],[object Object]
[email_address] Questions? Comments?

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