In its lucky 12+1 edition, during April 7-9, 2010, the European Conference on Genetic Programming (EuroGP) travelled to its most easterly location so far, theEuropeanCityof Culture2010,Istanbul,Turkey.EuroGPisthe onlyconf- enceworldwideexclusivelydevotedtogeneticprogrammingandtheevolutionary generation of computer programs. For over a decade, genetic programming (GP) has been considered the new form of evolutionary computation. With nearly 7,000 articles in the online GP bibliography maintained by William B. Langdon, we can say that it is now a mature ?eld. EuroGP has contributed to the success of the ?eld substantially, by being a unique forum for expressing new ideas, meeting, and starting up collaborations. The wide rangeoftopics in this volume re?ectthecurrentstateof researchin the ?eld, including representations, theory, operators and analysis, novel m- els, performance enhancements, extensions of genetic programming,and various applications. The volume contains contributions in the following areas: - Understanding GP behavior andGP analysis include articles on cro- over operators and a new way of analyzing results. -GPperformance presents work on performance enhancements through phenotypic diversity, simpli?cation, ?tness and parallelism. - Novel models and their application present innovative approaches with arti?cial biochemical networks, genetic regulatory networks and geometric di?erential evolution. - Grammatical evolution introduces advances in crossover, mutation and phenotype-genotype maps in this relatively new area. - Machine learning and data mining include articles that present data miningormachinelearningsolutionsusingGPandalsocombinedatamining and machine learning with GP. - Applications rangefromsolvingdi?erentialequations,routingproblems to ?le type detection, object-oriented testing, agents. This year we received 48 submissions, of which 47 were sent to the reviewers.

The 11th European Conference on Genetic Programming, EuroGP 2008, took place in Naples, Italy from 26 to 28 March in the University of Naples Congress Centre with spectacular views over the Gulf of Naples. This volume contains the papers for the 21 oral presentations and 10 posters that were presented during this time. A diverse array of topics were covered re?ecting the current state of research in the ?eld of Genetic Programming, including the latest work on representations, theory, operators and analysis, evolvable hardware, agents and numerous applications. A rigorous, double-blind peer review process was employed, with each s- mission reviewed by at least three members of the international Program C- mittee. In total 61 papers were submitted this year, making an acceptance rate of 34% for full papers, and an overall acceptance rate of 51% including posters. S- mission of papers and the reviewing process were greatly assisted by the use of the MyReview management software originally developed by Philippe Rigaux, Bertrand Chardon and other colleagues from the Universite Paris-Sud Orsay, France. We are especially grateful to Marc Schoenauer from INRIA, France for managing this system. Reviewers were asked to nominate keywords specifying their area of expertise, and these keywords were matched to those selected by the authors of the submitted papers with the assistance of the optimal assignment feature of the conference management software."

This book constitutes the refereed proceedings of the 10th European Conference on Genetic Programming, EuroGP 2007, held in Valencia, Spain in April 2007 colocated with EvoCOP 2007.

The 21 revised plenary papers and 14 revised poster papers were carefully reviewed and selected from 71 submissions. The papers address fundamental and theoretical issues, along with a wide variety of papers dealing with different application areas, such as chess game playing, real-time evaluation of VoIP, multi-objective optimization, evolution of recursive sorting algorithms, density estimation for inverse problem solving, image filter evolution, predicting prime numbers, data mining, grammatical genetic programming, layered learning, expression simplification, neutrality and evolvability, iterated function systems, particle swarm optimization, or open ended evolution. The use of Genetic Programming for several different applications shows that the method is a very general problem-solving paradigm.