Introduction to Genetic Programming
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Transcript of Introduction to Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
GENETIC PROGRAMING
Muhammad Adil Raja
Roaming Researchers, Inc
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
OUTLINE
1 INTRODUCTION
2 EXPERIMENTAL SETUP
3 GENETIC OPERATORS
4 APPLICATIONS
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
OUTLINE
1 INTRODUCTION
2 EXPERIMENTAL SETUP
3 GENETIC OPERATORS
4 APPLICATIONS
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
OUTLINE
1 INTRODUCTION
2 EXPERIMENTAL SETUP
3 GENETIC OPERATORS
4 APPLICATIONS
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
OUTLINE
1 INTRODUCTION
2 EXPERIMENTAL SETUP
3 GENETIC OPERATORS
4 APPLICATIONS
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
INTRODUCTION TO GENETIC PROGRAMMING (GP)
Genetic Programming is a coarse emulation of DarwinianEvolution.
The search space is composed of all the possiblecomputer programs.
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
GP Life Cycle: The Pseudo Code1 Create an initial population of computer programs.2 Evaluation.3 Selection.4 Reproduction.5 Evaluation.6 Replacement.7 Continue from 3.
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
A TYPICAL GP BREEDING CYCLE
FIGURE:Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
TABLE: Fiddle Parameters of a Typical GP Experiment
Parameter ValueInitial Population Size 300Initial Tree Depth 6Selection LPPTournament Size 2Genetic Operators Crossover and Subtree MutationOperators Probability Type AdaptiveInitial Operator probabilities 0.5 eachSurvival Half ElitismGeneration Gap 1Function Set plus, minus, multiply, divide,sin,
cos, log2, log10, loge , sqrt,power, if
Terminal Set Random real-valued numbersbetween 0.0 and 1.0. Integers (2–10) andNetwork traffic parameters from Table.
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
SELECTION
Roulette Wheel Selection – Fitness ProportionateSelection.
Tournament Selection.
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
CROSSOVER
log
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x * (tan y + z ) log (x + yz )
z
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*
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x * ( (x+yz) + z ) log (tan y)
tan
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offsprings
parents
Functions
Terminals
subtrees selected randomly for crossover
FIGURE:
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
MUTATION
log
log
tan z
+
y
x * (tan y + z ) log (x + yz )
*
x +
*
x *
y z
parents
Functions
subtrees selected randomly for crossover
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
SURVIVAL
Elitism
Replacement
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
FITNESS EVALUATION
Mean squared error (MSE).
Chi squared error.
Scaled mean squared error.
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
APPLICATIONS
Applications are quite too many.
GP as a hammer.
A hammer that finds everything else as a nail.
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
APPLICATIONS
In regression and classification.
Regression or Classification of nonlinear problems.
In Telecommunications: Speech quality estimation.
In Computer Networks: Network coding.
In Finance: In evolving effective bidding strategies.
In Clinical: Cancer detectors, seizure detectors, mentalhealth diagnosis etc.
Muhammad Adil Raja Genetic Programming
IntroductionExperimental Setup
Genetic OperatorsApplications
MORE APPLICATIONS
In evolving chess players.
In evolving antenna designs.
Evolvable hardware.
Muhammad Adil Raja Genetic Programming