GPEM 10(3) now available online

The third issue of volume 10 of Genetic Programming and Evolvable Machines is now available online, containing the following articles:

A three-step decomposition method for the evolutionary design of sequential logic circuits

by Houjun Liang, Wenjian Luo and Xufa Wang

Evolutionary design of evolutionary algorithms

by Laura Dioşan and Mihai Oltean

Semantic analysis of program initialisation in genetic programming

by Lawrence Beadle and Colin G. Johnson

Additional awards at GECCO-2009

There were several awards presented at the GECCO-2009 conference aside from the Human-Competitive Results Awards (Humies) awards about which Wolfgang posted previously, and for which I've listed the other winners below. Of particular interest to readers of this blog may be the Best Paper awards from each of the technical tracks; these are generally awarded for exciting new results, several of which may soon be appearing in more complete form in our field's journals. In addition, this year was the first year of the SIGEVO GECCO Impact Award, for the papers with the most citations from the GECCO conference 10 years ago.

Congratulations to all of the winners!

2009 SIGEVO GECCO Impact Awards, for the papers with the most citations from GECCO 1999

M. Pelikan, D. Goldberg, E. Cantu-Paz: "BOA: The Bayesian Optimization Algorithm"

Citations: 447

S. Hofmeyer, S. Forrest: "Immunity by Design: An Artificial Immune System"

Citations: 212

2009 "Humies" Awards for Human-Competitive Results Produced by Genetic and Evolutionary Computation

Humies BRONZE MEDALS

Perez, Olague: "Evolutionary Learning of Local Descriptor Operators for Object Recognition"

AND Hauptpman, Elyasay, Sipper, Karman: "GP to Evolve Solvers for the Rush Hour Problem"

Humies SILVER MEDAL

Shahzad, Zahid, Farooq, Khayam: "GA+PSO for User ID on Smart Phones"

Humies GOLD MEDAL

Forrest, Le Goues, Nguyen, Weimer: "GP for Automated Software Repair"

2009 GECCO Best Paper Awards

Ant Colony Optimization and Swarm Intelligence: "Parallel Shared Memory Strategies for Ant-Based Optimization Algorithms" by T. Bui, T. Nguyen, J. R. Rizzo Jr.

Artificial Life, Evolutionary Robotics, Adaptive Behavior, Evolvable Hardware: "How Novelty Search Escapes the Deceptive Trap of Learning to Learn" by S. Risi, S. D. Vanderbleek, C. E. Hughes, K. O. Stanley

Bioinformatics and Computational Biology Modeling: "Evolutionary Fitness for DNA Motif Discovery" by S. Rahmann, T. Marschall, F. Behler, O. Kramer

Combinatorial Optimization and Metaheuristics: "Fixed-Parameter Evolutionary Algorithms and the Vertex Cover Problem" by S. Kratsch, F. Neumann

Estimation of Distribution Algorithms: "EDA-RL: Estimation of Distribution Algorithms for Reinforcement Learning Problems" by H. Handa

AND

"Approximating the Search Distribution to the Selection Distribution in EDAs" by S. I. Valdez-Peña, A. Hernández-Aguirre, S. Botello-Rionda

Evolution Strategies and Evolutionary Programming: "Efficient Natural Evolution Strategies" by Y. Sun, D. Wierstra, T. Schaul, J. Schmidhuber

Evolutionary Multiobjective Optimization: "Multiplicative Approximations and the Hypervolume Indicator" by T. Friedrich, C. Horoba, F. Neumann

Generative and Developmental Systems: "The Sensitivity of HyperNEAT to Different Geometric Representations of a Problem" by J. Clune, C. Ofria, R. T. Pennock

Genetic Algorithms: "Tunneling Between Optima: Partition Crossover for the Traveling Salesman Problem" by D. Whitley, A. Howe, D. Hains

Genetic Programming: "A Genetic Programming Approach to Automated Software Repair" by S. Forrest, T.V. Nguyen, W. Weimer, C. Le Goues

Genetics-Based Machine Learning: "Learning Sensorimotor Control Structures with XCSF" by M. V. Butz, G. K. M. Pedersen, P. O. Stalph

AND

"New Entropy Model for Extraction of Structural Information from XCS Population" by W. K. Park, J. C. Oh

Parallel Evolutionary Systems: "Strategies to Minimise the Total Run Time of Cyclic Graph Based Genetic Programming with GPUs" by T. E. Lewis, G. D. Magoulas

Real World Applications: "Optimizing Low-Discrepancy Sequences with an Evolutionary Algorithm" by F.-M. De Rainville, C. Gagné, O. Teytaud, D. Laurendeau

Search Based Software Engineering: "Software Project Planning for Robustness and Completion Time in the Presence of Uncertainty using Multi Objective Search Based Software Engineering" by S. Gueorguiev, M. Harman, G. Antoniol

Theory: "Dynamic Evolutionary Optimisation: An Analysis of Frequency and Magnitude of Change" by P. Rohlfshagen. P. K. Lehre, X. Yao

GECCO Graduate Student Workshop: "Learnable Evolution Model Performance Impaired by Binary Tournament Survival Selection" by M. Coletti (George Mason University)

GECCO Humies Award (GOLD) 2009

GP was well featured at this year's GECCO Humies Awards. The most spectacular application which was subsequently awarded first prize (GOLD) was based on two papers by Weimer/Nguyen/Le Goues/Forrest
published in proceedings of the 31st International Conference on Software Engineering (ICSE) in May 2009 and Forrest/Weimer/Nguyen/Le Goes in this year's GECCO proceedings. Both papers won awards from the respective conferences, and winning the Humies award was the "icing on the cake".

The authors apply a specialized/improved form of Genetic Programming to locate and repair software bugs. Repairing software bugs is a time consuming and commercially very costly activity. To date, automating the process has been very difficult. The GP method proposed by our Gold Medal winners takes down the average repair time for software bugs from more than 3 hours per bug to 3 minutes.

The authors rightly claim that "showing how to use GP in the context of modern software systems and integrating GP into modern software practice will help evolutionary computation to become more widely accepted by computer scientists."

Congratulations to the authors for a prize well deserved!

Award for David E. Goldberg

David E. Goldberg has been awarded an Evolutionary Computation Pioneer Award by the Computational Intelligence Society. More details here. Well-deserved congratulations to David, who has given so much to our field!