Ebook: Genetic Programming Theory and Practice II
Author: Una-May O’Reilly Tina Yu Rick Riolo (auth.) Una-May O’Reilly Tina Yu Rick Riolo Bill Worzel (eds.)
- Tags: Theory of Computation, Computing Methodologies, Artificial Intelligence (incl. Robotics), Algorithm Analysis and Problem Complexity, Programming Techniques
- Series: Genetic Programming 8
- Year: 2005
- Publisher: Springer US
- Edition: 1
- Language: English
- pdf
This volume explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). The contributions developed from a second workshop at the University of Michigan's Center for the Study of Complex Systems where leading international genetic programming theorists from major universities and active practitioners from leading industries and businesses met to examine how GP theory informs practice and how GP practice impacts GP theory. Chapters include such topics as financial trading rules, industrial statistical model building, population sizing, the roles of structure in problem solving by computer, stock picking, automated design of industrial-strength analog circuits, topological synthesis of robust systems, algorithmic chemistry, supply chain reordering policies, post docking filtering, an evolved antenna for a NASA mission and incident detection on highways.
This volume explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). The contributions developed from a second workshop at the University of Michigan's Center for the Study of Complex Systems where leading international genetic programming theorists from major universities and active practitioners from leading industries and businesses met to examine how GP theory informs practice and how GP practice impacts GP theory. Chapters include such topics as financial trading rules, industrial statistical model building, population sizing, the roles of structure in problem solving by computer, stock picking, automated design of industrial-strength analog circuits, topological synthesis of robust systems, algorithmic chemistry, supply chain reordering policies, post docking filtering, an evolved antenna for a NASA mission and incident detection on highways.
This volume explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). The contributions developed from a second workshop at the University of Michigan's Center for the Study of Complex Systems where leading international genetic programming theorists from major universities and active practitioners from leading industries and businesses met to examine how GP theory informs practice and how GP practice impacts GP theory. Chapters include such topics as financial trading rules, industrial statistical model building, population sizing, the roles of structure in problem solving by computer, stock picking, automated design of industrial-strength analog circuits, topological synthesis of robust systems, algorithmic chemistry, supply chain reordering policies, post docking filtering, an evolved antenna for a NASA mission and incident detection on highways.
Content:
Front Matter....Pages i-xv
Genetic Programming: Theory and Practice....Pages 1-10
Discovering Financial Technical Trading Rules Using Genetic Programming with Lambda Abstraction....Pages 11-30
Using Genetic Programming in Industrial Statistical Model Building....Pages 31-48
Population Sizing for Genetic Programming Based on Decision-Making....Pages 49-65
Considering the Roles of Structure in Problem Solving by Computer....Pages 67-86
Lessons Learned Using Genetic Programming in a Stock Picking Context....Pages 87-102
Favourable Biasing of Function Sets Using Run Transferable Libraries....Pages 103-120
Toward Automated Design of Industrial-Strength Analog Circuits by Means of Genetic Programming....Pages 121-142
Topological Synthesis of Robust Dynamic Systems by Sustainable Genetic Programming....Pages 143-157
Does Genetic Programming Inherently Adopt Structured Design Techniques?....Pages 159-174
Genetic Programming of an Algorithmic Chemistry....Pages 175-190
ACGP: Adaptable Constrained Genetic Programming....Pages 191-206
Using Genetic Programming to Search for Supply Chain Reordering Policies....Pages 207-223
Cartesian Genetic Programming and the Post Docking Filtering Problem....Pages 225-244
Listening to Data: Tuning a Genetic Programming System....Pages 245-262
Incident Detection on Highways....Pages 263-282
Pareto-Front Exploitation in Symbolic Regression....Pages 283-299
An Evolved Antenna for Deployment on Nasa’s Space Technology 5 Mission....Pages 301-315
Back Matter....Pages 317-320
This volume explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). The contributions developed from a second workshop at the University of Michigan's Center for the Study of Complex Systems where leading international genetic programming theorists from major universities and active practitioners from leading industries and businesses met to examine how GP theory informs practice and how GP practice impacts GP theory. Chapters include such topics as financial trading rules, industrial statistical model building, population sizing, the roles of structure in problem solving by computer, stock picking, automated design of industrial-strength analog circuits, topological synthesis of robust systems, algorithmic chemistry, supply chain reordering policies, post docking filtering, an evolved antenna for a NASA mission and incident detection on highways.
Content:
Front Matter....Pages i-xv
Genetic Programming: Theory and Practice....Pages 1-10
Discovering Financial Technical Trading Rules Using Genetic Programming with Lambda Abstraction....Pages 11-30
Using Genetic Programming in Industrial Statistical Model Building....Pages 31-48
Population Sizing for Genetic Programming Based on Decision-Making....Pages 49-65
Considering the Roles of Structure in Problem Solving by Computer....Pages 67-86
Lessons Learned Using Genetic Programming in a Stock Picking Context....Pages 87-102
Favourable Biasing of Function Sets Using Run Transferable Libraries....Pages 103-120
Toward Automated Design of Industrial-Strength Analog Circuits by Means of Genetic Programming....Pages 121-142
Topological Synthesis of Robust Dynamic Systems by Sustainable Genetic Programming....Pages 143-157
Does Genetic Programming Inherently Adopt Structured Design Techniques?....Pages 159-174
Genetic Programming of an Algorithmic Chemistry....Pages 175-190
ACGP: Adaptable Constrained Genetic Programming....Pages 191-206
Using Genetic Programming to Search for Supply Chain Reordering Policies....Pages 207-223
Cartesian Genetic Programming and the Post Docking Filtering Problem....Pages 225-244
Listening to Data: Tuning a Genetic Programming System....Pages 245-262
Incident Detection on Highways....Pages 263-282
Pareto-Front Exploitation in Symbolic Regression....Pages 283-299
An Evolved Antenna for Deployment on Nasa’s Space Technology 5 Mission....Pages 301-315
Back Matter....Pages 317-320
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