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Beskrivning
These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP.
Application of Machine-Learing Methods to Understand Gene Expression Regulation.- Identification of Novel Genetic Models of Glaucoma using the "Emergent" Genetic Programming-Based Artificial Intelligence System.- Inheritable Epigenetics in Genetic Programming.- SKGP: The Way of the Combinator.- Sequential Symbolic Regression with Genetic Programming.- Sliding Window Symbolic Regression for Detecting Changes of System Dynamics.- Extremely Accurate Symbolic Regression for Large Feature Problems.- How to Exploit Alignment in the Error Space: Two Different GP Models.- Analyzing a Decade of Human-Competitive ("HUMIE") Winners: What Can We Learn?.- Tackling the Boolean Multiplexer Function Using a Highly Distributed Genetic Programming System.
Wolfgang Banzhaf, Betty H.C. Cheng, Kalyanmoy Deb, Kay E. Holekamp, Richard E. Lenski, Charles Ofria, Robert T. Pennock, William F. Punch, Danielle J. Whittaker