Probabilistic Grammatical Evolution

Grammatical Evolution (GE) is one of the most popular Genetic Programming (GP) variants, and it has been used with success in several problem domains. Since the original proposal, many enhancements have been proposed to GE in order to address some of its main issues and improve its performance.

[1]  Grant Dick,et al.  Examining the "Best of Both Worlds" of Grammatical Evolution , 2015, GECCO.

[2]  Alexandros Agapitos,et al.  Understanding Grammatical Evolution: Grammar Design , 2018, Handbook of Grammatical Evolution.

[3]  Leonardo Vanneschi,et al.  Genetic programming needs better benchmarks , 2012, GECCO '12.

[4]  Nuno Lourenço,et al.  A Comparative Study of Different Grammar-Based Genetic Programming Approaches , 2017, EuroGP.

[5]  Peter A. Whigham,et al.  Grammatically-based Genetic Programming , 1995 .

[6]  Conor Ryan.  A rebuttal to Whigham, Dick, and Maclaurin by one of the inventors of Grammatical Evolution: Commentary on “On the Mapping of Genotype to Phenotype in Evolutionary Algorithms” by Peter A. Whigham, Grant Dick, and James Maclaurin , 2017, Genetic Programming and Evolvable Machines.

[7]  Hyun-Kyu Kang,et al.  A Conditional Dependency Based Probabilistic Model Building Grammatical Evolution , 2016, IEICE Trans. Inf. Syst..

[8]  Conor Ryan,et al.  Grammatical evolution , 2007, GECCO '07.

[9]  Maarten Keijzer,et al.  Grammatical Evolution Rules: The Mod and the Bucket Rule , 2002, EuroGP.

[10]  Nuno Lourenço,et al.  Unveiling the properties of structured grammatical evolution , 2016, Genetic Programming and Evolvable Machines.

[11]  Michael O'Neill,et al.  Grammatical Evolution: Evolving Programs for an Arbitrary Language , 1998, EuroGP.

[12]  Miguel Nicolau.  Understanding grammatical evolution: initialisation , 2017, Genetic Programming and Evolvable Machines.

[13]  Chang Wook Ahn,et al.  A New Grammatical Evolution Based on Probabilistic Context-free Grammar , 2015 .

[14]  Anthony Brabazon,et al.  pi-Grammatical Evolution , 2004, GECCO.

[15]  Pedro Larrañaga,et al.  Estimation of Distribution Algorithms , 2002, Genetic Algorithms and Evolutionary Computation.

[16]  J. A. Lozano,et al.  Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation , 2001 .

[17]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[18]  Eric Medvet,et al.  Weighted Hierarchical Grammatical Evolution , 2020, IEEE Transactions on Cybernetics.

[19]  J. A. Lozano,et al.  Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms (Studies in Fuzziness and Soft Computing) , 2006 .

[20]  Michael O'Neill,et al.  No Coercion and No Prohibition, a Position Independent Encoding Scheme for Evolutionary Algorithms - The Chorus System , 2001, EuroGP.

[21]  Nguyen Xuan Hoai,et al.  Probabilistic model building in genetic programming: a critical review , 2013, Genetic Programming and Evolvable Machines.

[22]  Anthony Brabazon,et al.  An Analysis of Genotype-Phenotype Maps in Grammatical Evolution , 2010, EuroGP.

[23]  Li Li,et al.  Maximum relevance minimum common redundancy feature selection for nonlinear data , 2017, Inf. Sci..

[24]  Franz Rothlauf,et al.  On the Locality of Grammatical Evolution , 2006, EuroGP.