附註:Includes bibliographical references and index.
Genetic programming: theory and practice / Una-May O'Reilly [and others] -- Discovering financial technical trading rules using genetic programming with lambda abstraction / Tina Yu, Shu-Heng Chen and Tzu-Wen Kuo -- Using genetic programming in industrial statistical model building / Flor Castillo [and others] -- Population sizing for genetic programming based on decision-making / Kumara Sastry, Una-May O'Reilly and David E. Goldberg -- Considering the roles of structure in problem solving by computer / Jason Daida -- Lessons learned using genetic programming in a stock picking context / Michael Caplan and Ying Becker -- Favourable biasing of function sets / Conor Ryan, Maarten Keijzer, and Mike Cattolico -- Toward automated design of industrial-strength analog circuits by means of genetic programming / J.R. Koza [and others] -- Topological synthesis of robust dynamic systems by sustainable genetic programming / Jianjun Hu and Erik Goodman -- Does genetic programming inherently adopt structured design techniques? / John M. Hall and Terence Soule -- Genetic programming of an algorithmic chemistry / W. Banzhaf and C. Lasarczyk -- ACGP: Adaptable Constrained Genetic Programming / Cezary Z Janikow -- Using genetic programming to search for supply chain reordering policies / Scott A. Moore and Kurt DeMaagd -- Cartesian genetic programming and the post docking filtering problem / A. Beatriz Garmendia-Doval, Julian F Miller, and S. David Morley -- Listening to data: tuning a genetic programming system / Duncan MacLean, Eric A. Wollesen and Bill Worzel -- Incident detection on highways / Daniel Howard and Simon C. Roberts -- Pareto-front exploitation in symbolic regression / Guido F Smits and Mark Kotanchek -- An evolved antenna for deployment on NASA's Space Technology 5 mission / Jason D. Lohn, Gregory S. Hornby, and Derek S. Linden.
摘要: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.
