Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
A compiling genetic programming system that directly manipulates the machine code
Advances in genetic programming
Biomimetic Representation with Genetic Programming Enzyme
Genetic Programming and Evolvable Machines
Crossover in Grammatical Evolution
Genetic Programming and Evolvable Machines
ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence)
Evolutionary morphogenesis for multi-cellular systems
Genetic Programming and Evolvable Machines
Evolving modular genetic regulatory networks
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Putting more genetics into genetic algorithms
Evolutionary Computation
The challenge of irrationality: fractal protein recipes for PI
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Structural and nodal mutation in grammatical evolution
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Hybrid modeling and simulation of genetic regulatory networks
HSCC'03 Proceedings of the 6th international conference on Hybrid systems: computation and control
Grammar-based Genetic Programming: a survey
Genetic Programming and Evolvable Machines
Using feedback in a regulatory network computational device
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Evolving genes to balance a pole
EuroGP'10 Proceedings of the 13th European conference on Genetic Programming
The Regulatory Network Computational Device
Genetic Programming and Evolvable Machines
Applying genetic regulatory networks to index trading
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Differential gene expression with tree-adjunct grammars
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
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The Central Dogma of Biology states that genes made proteins that made us. This principle has been revised in order to incorporate the role played by a multitude of regulatory mechanisms that are fundamental in both the processes of inheritance and development. Evolutionary Computation algorithms are inspired by the theories of evolution and development, but most of the computational models proposed so far rely on a simple genotype to phenotype mapping. During the last years some researchers advocate the need to explore computationally the new biological understanding and have proposed different gene expression models to be incorporated in the algorithms.Two examples are the Artificial Regulatory Network (ARN) model, first proposed by Wolfgang Banzhaf, and the Grammatical Evolution (GE) model, introduced by Michael O'Neill and Conor Ryan. In this paper, we show how a modified version of the ARN can be combined with the GE approach, in the context of automatic program generation. More precisely, we rely on the ARN to control the gene expression process ending in an ordered set of proteins, and on the GE to build, guided by a grammar, a computational structure from that set. As a proof of concept we apply the hybrid model to two benchmark problems and show that it is effective in solving them.