Alberto Moraglio
Krzysztof Krawiec
- A. Moraglio, K. Krawiec, C. Johnson, Geometric Semantic Genetic Programming, PPSN XII, 2012. Google Scholar
Digital Library
- K. Krawiec, P. Lichocki, Approximating Geometric Crossover in Semantic Space, GECCO 2009, Google ScholarDigital Library
- K. Krawiec, T. Pawlak, Locally Geometric Semantic Crossover: A Study on the Roles of Semantic and Homology in Recombination Operators, Genetic Programming and Evolvable Machines, 2013, Google ScholarDigital Library
- T. Pawlak, B. Wieloch, K. Krawiec, Semantic Backpropagation for Designing Genetic Operators in Genetic Programming, IEEE Transactions on Evolutionary Computation, 2014.Google Scholar
- L. Beadle, C. Johnson, Semantically Driven Crossover in Genetic Programming, CEC 2008, Google ScholarDigital Library
- L. Beadle, C. Johnson, Semantically Driven Mutation in Genetic Programming, CEC 2009, Google ScholarDigital Library
- N.Q. Uy, N.X. Hoai, M. O'Neill, R.I. McKay, E. Galvan-Lopez, Semantically-based crossover in genetic programming: application to real-valued symbolic regression, Genetic Programming and Evolvable Machines, 2011, Google ScholarDigital Library
- N.Q. Uy, N.X. Hoai, M. O'Neill, R.I. McKay, D.N. Phong, On the roles of semantic locality in genetic programming, Information Sciences, 2013, Google ScholarDigital Library
- N.Q. Uy, N.X. Hoai, Michael O'Neill, Semantics based mutation in genetic programming: The case for real-valued symbolic regression, MENDEL 2009.Google Scholar
- L. Beadle, C. Johnson, Semantic analysis of program initialisation in genetic programming, Genetic Programming and Evolvable Machines, 2009, Google ScholarDigital Library
- D. Jackson, Promoting Phenotypic Diversity in Genetic Programming, PPSN XI, 2010. Google ScholarDigital Library
- E. Galvan-Lopez, B. Cody-Kenny, L. Trujillo, A. Kattan, Using Semantics in the Selection Mechanism in Genetic Programming: a Simple Method for Promoting Semantic Diversity, CEC 2013.Google ScholarCross Ref
- R.E. Smith, S. Forrest, and A.S. Perelson. "Searching for diverse, coop- erative populations with genetic algorithms". In: Evolutionary Computation 2 (1993). Google ScholarDigital Library
- Lasarczyk, C. W. G. & and Wolfgang Banzhaf, P. D. Dynamic Subset Selection Based on a Fitness Case Topology Evolutionary Computation, 2004, 12, 223--242 Google ScholarDigital Library
- Nguyen Quang Uy, Nguyen Xuan Hoai, Michael O'Neill, R. I. McKay, and Dao Ngoc Phong. On the roles of semantic locality of crossover in genetic programming. Information Sciences, 235:195--213, 20 June 2013. Google ScholarDigital Library
- Mauro Castelli, Leonardo Vanneschi, and Sara Silva. Semantic search-based genetic programming and the effect of intron deletion. IEEE Transactions on Cybernetics, 44(1):103--113, January 2014.Google ScholarCross Ref
- Langdon, W. B. & Poli, R. Foundations of Genetic Programming Springer-Verlag, 2002 Google ScholarDigital Library
- McPhee, N. F., Ohs, B. & Hutchison, T., Semantic Building Blocks in Genetic Programming, in O'Neill, M et al. (eds.) Proceedings of the 11th European Conference on Genetic Programming, EuroGP 2008, Springer, 2008, 4971, 134--145 Google ScholarDigital Library
- A. Moraglio, Towards a Geometric Unification of Evolutionary Algorithms, PhD Thesis, University of Essex, UK, 2007.Google Scholar
- A. Moraglio, R. Poli, Topological Interpretation of Crossover, Genetic and Evolutionary Computation Conference, pages 1377--1388, 2004.Google Scholar
- A. Moraglio, A. Mambrini, L. Manzoni, Runtime Analysis of Mutation-Based Geometric Semantic Geometric Programming on Boolean Functions, Foundations of Genetic Algorithms, 2013. Google ScholarDigital Library
- A. Moraglio, A. Mambrini, Runtime Analysis of Mutation-Based Geometric Semantic Genetic Programming for Basis Functions Regression, Genetic and Evolutionary Computation Conference, 2013. Google ScholarDigital Library
- A. Mambrini, L. Manzoni, A. Moraglio, Theory-Laden Design of Mutation-Based Geometric Semantic Genetic Programming for Learning Classification Trees, IEEE Congress on Evolutionary Computation 2013.Google Scholar
- A. Moraglio, J. McDermott, M. O'Neill, Geometric Semantic Grammatical Evolution, SMGP workshop at PPSN, 2014.Google Scholar
- A. Moraglio, An Efficient Implementation of GSGP using Higher-Order Functions and Memoization, SMGP workshop at PPSN, 2014.Google Scholar
- J. Fieldsend, A. Moraglio. Strength through diversity: Disaggregation and multi-objectivisation approaches for genetic programming, GECCO, 2015 (to appear). Google ScholarDigital Library
- L. Vanneschi, M. Castelli, L. Manzoni, S. Silva, A New Implementation of Geometric Semantic GP and Its Application to Problems in Pharmacokinetics, EuroGP 2013 Google ScholarDigital Library
- L. Vanneschi, S. Silva, M. Castelli, L. Manzoni, Geometric semantic genetic programming for real life applications, in Genetic Programming Theory and Practice XI, 2013Google Scholar
- R. Ffrancon, M. Schoenauer, Greedy Semantic Local Search for Small Solutions, Semantic Methods in Genetic Programming Workshop, GECCO'15, 2015. Google ScholarDigital Library
- T.P. Pawlak, Competent Algorithms for Geometric Semantic Genetic Programming, PhD Thesis, Poznan University of Technology, 2015.Google Scholar
- T.P. Pawlak, K. Krawiec, Progress properties and fitness bounds for geometric semantic search operators, Genetic Programming and Evolvable Machines, Vol. 17, pp. 5--23, March 2016. Google ScholarDigital Library
Index Terms
- Semantic Genetic Programming
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