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(10)   

• A quantitative study of neutrality in GP boolean landscapes
  Leonardo Vanneschi and Yuri Pirola and Philippe Collard GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation, 1, page895--902. Seattle, Washington, USA, ACM Press, 8-12 July2006.
  to neutrality, programming, measures, fitness performance genetic complexity even measures algorithms, landscapes, parity, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• A Study of Fitness Distance Correlation as a Difficulty Measure in Genetic Programming
  Marco Tomassini and Leonardo Vanneschi and Philippe Collard and Manuel Clergue Evolutionary Computation13(2):213--239Summer2005.
  to distance programming, fitness difficulty, program genetic problem correlation algorithms, landscapes, by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Principles in the Evolutionary Design of Digital Circuits-Part II
  Julian F. Miller and Dominic Job and Vesselin K. Vassilev Genetic Programming and Evolvable Machines1(3):259--288July2000.
  to computing, fitness reasoning, design, evolvable extraction landscapes, digital principle programming, hardware, genetic evolutionary circuit circuits, algorithms, case based by brazovayeye and 1 other person on Jun 19, 2008, 5:46 PM
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• Digital Circuit Evolution and Fitness Landscapes
  Vesselin K. Vassilev and Julian F. Miller and Terence C. Fogarty Proceedings of the Congress on Evolutionary Computation, 2, Mayflower Hotel, Washington D.C., USA, IEEE Press, 6-9 July1999.
  to evolution, fitness optimisation, genotype engineering digital landscapes, characteristics, search, programmable sequences, idealised connectivity, evolutionary alphabets, computation, field-programmable problems, cell sequences array, correlation arrays, logic gate field functionality, combinatorial problem, circuits, circuit representation, model, optimisation by brazovayeye on Jun 19, 2008, 5:35 PM
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• Evolving Problems to Learn about Particle Swarm Optimisers and other Search Algorithms
  W. B. Langdon and Riccardo Poli IEEE Transactions on Evolutionary Computation11(5):561--578October2007.
  to swarms fitness (DE), DE, landscapes, CMA-ES, evolution Differential search, particle XPS, programming, PSO, genetic algorithms, local hill-climbers, by brazovayeye on Jun 19, 2008, 5:35 PM
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• Convergence of Program Fitness Landscapes
  W. B. Langdon Genetic and Evolutionary Computation -- GECCO-2003, volume2724ofLNCS, page1702--1714. Chicago, Springer-Verlag, 12-16 July2003.
  to computer computing, fitness mutation, Neighborhood, landscapes, programming programming, computer, boolean proof, algorithms, amorphous flip hill linear climbing, function, random general runtime, bit point expected route genetic modulo reversible average map, by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• Convergence Rates for the Distribution of Program Outputs
  W. B. Langdon GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, page812--819. New York, Morgan Kaufmann Publishers, 9-13 July2002.
  to Fitness computer Landscapes, analysis, Minorization, Markov eigenvalues, time, programming, genetic Variation convergence Average algorithms, Random walk Mutation Distance, Total by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• Scaling of Program Tree Fitness Spaces
  W. B. Langdon Evolutionary Computation7(4):399--428Winter1999.
  to sampling, Carlo Fe regression, fitness gates, trail, symbolic stochastic landscapes, search, Monte tree programming, genetic nand Santa algorithms, ant artificial by brazovayeye on Jun 19, 2008, 5:35 PM
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• Fitness Landscapes and Difficulty in Genetic Programming
  Kenneth E. Kinnear, Jr. Proceedings of the 1994 IEEE World Conference on Computational Intelligence, 1, page142--147. Orlando, Florida, USA, IEEE Press, 27-29 June1994.
  to problems, basin adaptive fitness depths, random (artificial autocorrelation, learning landscape landscapes, algorithm intelligence), walks walks, programming, measures, search genetic algorithms, theory, by brazovayeye and 1 other person on Jun 19, 2008, 5:35 PM
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• What Makes a Problem GP-Hard? Analysis of a Tunably Difficult Problem in Genetic Programming
  Jason M. Daida and Robert R. Bertram and Stephen A. Stanhope and Jonathan C. Khoo and Shahbaz A. Chaudhary and Omer A. Chaudhri and John A. Polito II Genetic Programming and Evolvable Machines2(2):165--191June2001.
  to problems, programming, test fitness difficulty, genetic GP theory problem algorithms, landscapes, by brazovayeye on Jun 19, 2008, 5:35 PM
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