Genetic Programming

Name: Genetic Programming | 14th European Conference, EuroGP 2011, Torino, Italy, April 27-29, 2011, Proceedings
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14th European Conference, EuroGP 2011, Torino, Italy, April 27-29, 2011, Proceedings

Sara Silva James A. Foster Miguel Nicolau Penousal Machado Mario Giacobini(Herausgeber*in)

Springer (Verlag)

Erschienen am 27. April 2011

XIII, 348 Seiten

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Inhalt

Title
Preface
Organization
Table of Contents
Oral Presentations
A Sniffer Technique for an Efficient Deduction of Model Dynamical Equations Using Genetic Programming
Introduction
Sniffer Enhanced GP Search Technique
Deduction of Model Differential Equations
Deduction of Chemical Reaction Model Equations
Deduction of a Special Function ODE
Deduction of KdV Equation
Conclusion and Outlook
References
Robustness, Evolvability, and Accessibility in Linear Genetic Programming
Introduction
Methods
Linear Genetic Programming
Genotype and Phenotype Networks
Robustness, Evolvability, and Accessibility
Results
Statistical Characteristics of Genotype and Phenotype Space
Random Walks through Genotype and Phenotype Space
Discussion
References
A Quantitative Study of Learning and Generalization in Genetic Programming
Introduction
Previous and Related Work
The Proposed Measures
Test Problems
Experimental Study
Conclusions and Future Work
References
GP-Based Electricity Price Forecasting
Introduction
Our Approach
Overview
GP Approach
Hybrid Approach
Experimental Evaluation
Dataset and Baseline
Settings
Results
Concluding Remarks
References
Novel Loop Structures and the Evolution of Mathematical Algorithms
Introduction
Related Work
LoopRepresentations
Test Problems
Experiments
Experimental Protocol
Results in Terms of Fitness
Results in Terms of Loop Effectiveness
The Evolution of the Loop Utilization
Conclusions
References
Maximum Margin Decision Surfaces for Increased Generalisation in Evolutionary Decision Tree Learning
Introduction
Model Generalisation in Genetically Programmed DTs
Geometry of a Linear Discriminant Function
Evolutionary Optimisation of a Maximum Margin Decision Surface via an ES(1+1)
Methods
Experimental Approach
Grammar-Based Genetic Programming
Results
Conclusion
References
Evolving Cell Array Configurations Using CGP
Introduction
Motivation and Related Work
Description of Cell Array
CGP Overview
Adaptation of CGP for Cell Array Evolution
Basic Operation Changes
Additional Genetic Operator, Node-Copy
Applying Selection Pressure for Parsimony
Performance Experiments
Results and Discussion
Comparison to Similar Techniques
Node-Copy
Size-Sort
Conclusions and Further Work
References
Designing Pheromone Update Strategies with Strongly Typed Genetic Programming
Introduction
ACO Algorithms
Evolving Pheromone Trail Update Methods
Strongly Typed Genetic Programming Engine
Related Work
Experiments and Analysis
Evolution of the Update Strategies
Validation and Comparison with Max-Min Ant System
Conclusions
References
Random Lines: A Novel Population Set-Based Evolutionary Global Optimization Algorithm
Introduction
Formulation
Performance Evaluation
Conclusion
References
A Peer-to-Peer Approach to Genetic Programming
Introduction
Description of the Model
Neighbor Selection Policy: Newscast
Experimental Setup and Results
Conclusions and Future Works
References
Performance Models for Evolutionary Program Induction Algorithms Based on Problem Difficulty Indicators
Introduction
Related Work
Algorithm Selection and Portfolios
Models of Performance for Evolutionary Algorithms
Modelling EPA's Performance
Can NSC and FDC Be Used in Performance Models?
Difficulty Indicators for Boolean Functions
Difficulty Indicators for Continuous Functions
Difficulty-Indicators Models
Model Identification
Test Problems and Systems
Results
Eliciting Knowledge from Our Models
Conclusions
References
Examining Mutation Landscapes in Grammar Based Genetic Programming
Introduction
Landscapes
Grammatical Evolution
Grammatical Evolution by Example
Tree-Adjunct Grammatical Evolution
Tree-Adjunct Grammatical Evolution by Example
Experiments and Results
Experimental Setup
Problems
Visualisations
Discussion
Conclusions
References
ReNCoDe: A Regulatory Network Computational Device
Introduction
Banzhaf's ARN
Architecture
Problems and Experimental Setup
Results and Analysis
Conclusions and Future Work
References
Statistical Distribution of Generation-to-Success in GP: Application to Model Accumulated Success Probability
Introduction
Initial Definitions
A General Model of Accumulated Success Probability
Empirical Model of Generation-to-Success
A Specific Model of Accumulated Success Probability
Experimental Validation of the Model of Accumulated Success Probability
Discussion
Related Work
Conclusions and Future Work
References
Learnable Embeddings of Program Spaces
Introduction
Programs, Semantics, and Locality of Semantic Mapping
Example 1: Semantic Locality of Symbolic Regression Program Spaces
Embedding Programs in Prespaces
Example 2: Learning Prespaces for Symbolic Regression
Learnable Embeddings and Prespaces as Tools for Search
Discussion
References
Parallel Linear Genetic Programming
Introduction
Objectives
Organization
Background
LGP
Classification
Classification Using LGP
Parallel LGP
Motivation
Program Structure
Crossover for PLGP
Experimental Setup
Data Sets
Parameter Configurations
Results
Discussion
Conclusions and Future Work
References
How Far Is It from Here to There? A Distance That Is Coherent with GP Operators
Introduction
Definitions
Discussion of Definitions w.r.t. Previous Work
Methods
Representation
Calculation of 1STP for Subtree Mutation
Calculation of Graph-Based Distances
Creating and Sampling from Sub-graphs
Calculation of Syntactic Distances
Results: Relationships among Distance Functions
Distribution of DMSTP
Learning DMSTP as a Function of Syntactic Distances
Relationships among Graph-Based Distances
Conclusions
References
Evolution of a Brain-Computer Interface Mouse via Genetic Programming
Introduction
BCI Mouse
GP System and Parameter Settings
Experimental Results
Conclusions
References
Operator Self-adaptation in Genetic Programming
Introduction
Background
Operator Parameter Adaptation
Tree Adjoining Grammars and Genetic Programming
Methods
Problems
Defining the LTAG3P System
Adaptive Mechanisms
Evolutionary Parameters
Results
Overall Performance
Operator Application Rates
Discussion
Conclusions
Summary
Limitations
Further Work
References
Evolving Fitness Functions for Mating Selection
Introduction
State of the Art
Other Approaches
Evolving the Fitness Function
Circle Packing in Squares
Mating Selection
Mating Selection in the Circle Packing in Squares Problem
Experimental Setup
Experimental Results
Conclusions
References
Posters
Experiments on Islands
Introduction
LGP System Used
The Test Cases
Intertwined Spirals
Regression
8-Bit Parity
Topology Experiments
Test Results
Delaying Migrations
Conclusion
References
A New Approach to Solving 0-1 Multiconstraint Knapsack Problems Using Attribute Grammar with Lookahead
Introduction
AGs
Multiconstraint Knapsack Problem
Previous Work
Grammatical Evolution Approaches for the MKP
AG with Lookahead for the MKP
Experiments
Results
Conclusions and Future Work
References
An Empirical Study of Functional Complexity as an Indicator of Overfitting in Genetic Programming
Introduction
Overfitting
Program Complexity
Functional Complexity
Experiments
Summary and Concluding Remarks
References
Estimating Classifier Performance with Genetic Programming
Introduction
Related Work
Problem Statement
GP Approach
Search Space
Fitness Function
Experiments
Experimental Setup and Data-Sets
Results and Comparisons
Summary and Concluding Remarks
References
Investigation of the Performance of Different Mapping Orders for GE on the Max Problem
Introduction
Grammatical Evolution Essentials
Genotype-Phenotype Maps - GE, GE
Experimental Setup
The Max Problem
Mappers
Results
Discussion
Conclusions and Future Work
References
A Self-scaling Instruction Generator Using Cartesian Genetic Programming
Introduction
CGP Decode for Instruction Generation
Dual-Layer CGP Architecture
Special Function Node
Extended Parametric CGP
Experiments
Settings
Results
Conclusions and Future Work
References
Exploring Grammatical Modification with Modules in Grammatical Evolution
Introduction
Previous Work
Experimental Setup
Results and Discussion
Grammar Modification
Grammar Enhancement and Fitness
Conclusion and Future Work
References
Multi-objective Genetic Programming for Visual Analytics
Introduction
The Multi-objective Genetic Programming Projection Pursuit (MOG3P) Algorithm
Feature Extraction Criteria
Standard Methods
MOG3P Multi-objective Criteria
Experiments
Conclusions
References
A Continuous Approach to Genetic Programming
Introduction
Differential Evolution
Linear Differential Evolutionary Programming
Representation
Implementation
Symbolic Regression and Artifical Ant Experiments
Symbolic Regression Problems
Santa Fe Ant Trail
Evolving a Stack with LDEP
Architecture and Fitness Function
Conclusion and Future Works
References
Author Index

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