10. EuroGP 2007: Valencia, Spain

• Erik Hemberg, Conor Gilligan, Michael O'Neill, Anthony Brabazon:
  A Grammatical Genetic Programming Approach to Modularity in Genetic Algorithms. 1-11
  
• Denis Robilliard, Virginie Marion-Poty, Sébastien Mahler, Cyril Fonlupt:
  An Empirical Boosting Scheme for ROC-Based Genetic Programming Classifiers. 12-22
  
• Matthew Walker, Howard Edwards, Chris H. Messom:
  Confidence Intervals for Computational Effort Comparisons. 23-32
  
• Maarten Keijzer, James Foster:
  Crossover Bias in Genetic Programming. 33-44
  
• Michael Defoin-Platel, Sébastien Vérel, Manuel Clergue, Malik Chami:
  Density Estimation with Genetic Programming for Inverse Problem Solving. 45-54
  
• William D. Smart, Peter Andreae, Mengjie Zhang:
  Empirical Analysis of GP Tree-Fragments. 55-67
  
• Anargyros Sarafopoulos, Bernard Buxton:
  Empirical Comparison of Evolutionary Representations of the Inverse Problem for Iterated Function Systems. 68-77
  
• Ami Hauptman, Moshe Sipper:
  Evolution of an Efficient Search Algorithm for the Mate-In-N Problem in Chess. 78-89
  
• Simon Harding, Wolfgang Banzhaf:
  Fast Genetic Programming on GPUs. 90-101
  
• Kenneth L. Holladay, Kay Robbins, Jeffery von Ronne:
  FIFTH^TM: A Stack Based GP Language for Vector Processing. 102-113
  
• Colin G. Johnson:
  Genetic Programming with Fitness Based on Model Checking. 114-124
  
• Alberto Moraglio, Cecilia Di Chio, Riccardo Poli:
  Geometric Particle Swarm Optimisation. 125-136
  
• Peter Lichodzijewski, Malcolm I. Heywood:
  GP Classifier Problem Decomposition Using First-Price and Second-Price Auctions. 137-147
  
• David Jackson, Adrian P. Gibbons:
  Layered Learning in Boolean GP Problems. 148-159
  
• Gianluigi Folino, Clara Pizzuti, Giandomenico Spezzano:
  Mining Distributed Evolving Data Streams Using Fractal GP Ensembles. 160-169
  
• Cyril De Fillon, Alberto Bartoli:
  Multi-objective Genetic Programming for Improving the Performance of TCP. 170-180
  
• Richard M. Downing:
  On Population Size and Neutrality: Facilitating the Evolution of Evolvability. 181-192
  
• Riccardo Poli, William B. Langdon, Stephen Dignum:
  On the Limiting Distribution of Program Sizes in Tree-Based Genetic Programming. 193-204
  
• James Alfred Walker, Julian Francis Miller:
  Predicting Prime Numbers Using Cartesian Genetic Programming. 205-216
  
• Adil Raja, R. Muhammad Atif Azad, Colin Flanagan, Conor Ryan:
  Real-Time, Non-intrusive Evaluation of VoIP. 217-228
  
• Michal Lemczyk, Malcolm I. Heywood:
  Training Binary GP Classifiers Efficiently: A Pareto-coevolutionary Approach. 229-240
  

Posters

• Leonardo Vanneschi, Marco Tomassini, Philippe Collard, Sébastien Vérel, Yuri Pirola, Giancarlo Mauri:
  A Comprehensive View of Fitness Landscapes with Neutrality and Fitness Clouds. 241-250
  
• Jungseok Shin, Moonyoung Kang, Robert I. McKay, Nguyen Xuan Hoai, Tuan Hao Hoang, Naoki Mori, Daryl Essam:
  Analysing the Regularity of Genomes Using Compression and Expression Simplification. 251-260
  
• James Alfred Walker, Julian Francis Miller:
  Changing the Genospace: Solving GA Problems with Cartesian Genetic Programming. 261-270
  
• Lidia Yamamoto:
  Code Regulation in Open Ended Evolution. 271-280
  
• Victor Ciesielski, Xiang Li:
  Data Mining of Genetic Programming Run Logs. 281-290
  
• Alexandros Agapitos, Simon M. Lucas:
  Evolving a Statistics Class Using Object Oriented Evolutionary Programming. 291-300
  
• Alexandros Agapitos, Simon M. Lucas:
  Evolving Modular Recursive Sorting Algorithms. 301-310
  
• Karel Slaný, Lukás Sekanina:
  Fitness Landscape Analysis and Image Filter Evolution Using Functional-Level CGP. 311-320
  
• Domagoj Jakobovic, Leonardo Jelenkovic, Leo Budin:
  Genetic Programming Heuristics for Multiple Machine Scheduling. 321-330
  
• Cecilia Di Chio, Paolo Di Chio:
  Group-Foraging with Particle Swarms and Genetic Programming. 331-340
  
• Edgar Galván López, Katya Rodríguez-Vázquez:
  Multiple Interactive Outputs in a Single Tree: An Empirical Investigation. 341-350
  
• Ivanoe De Falco, Antonio Della Cioppa, Domenico Maisto, Umberto Scafuri, Ernesto Tarantino:
  Parsimony Doesn't Mean Simplicity: Genetic Programming for Inductive Inference on Noisy Data. 351-360
  
• James Decraene, George G. Mitchell, Barry McMullin, Ciaran Kelly:
  The Holland Broadcast Language and the Modeling of Biochemical Networks. 361-370
  
• Amashini Naidoo, Nelishia Pillay:
  The Induction of Finite Transducers Using Genetic Programming. 371-380
  

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