C. Ryan

Publications280
h-index31
Citations5,248
Highly Influential Citations310
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Grammatical evolution - evolutionary automatic programming in an arbitrary language
TLDR
Grammatical Evolution is the first comprehensive introduction to Grammatical Evolution, a novel approach to Genetic Programming that adopts principles from molecular biology in a simple and useful manner, coupled with the use of grammars to specify legal structures in a search.
Grammatical Evolution: Evolving Programs for an Arbitrary Language
We describe a Genetic Algorithm that can evolve complete programs. Using a variable length linear genome to govern how a Backus Naur Form grammar definition is mapped to a program, expressions and…
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Grammatical evolution
  • C. Ryan
  • Computer Science, Linguistics
    GECCO '07
  • 7 July 2007
TLDR
This tutorial gives a brief introduction to Backus Naur Form Grammars and a background into the use of grammars with Genetic Programming, before describing the inner workings of Grammatical Evolution and some of the more commonly used extensions.
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Grammatical Evolution
A Genetic Algorithm is described that can evolve complete programs. U sing a variable length, linear, binary genome to govern the mapping of a Backus Naur Form gramm ar definition to a program,…
View on Springer
Grammatical evolution
TLDR
Grammatical evolution is presented, an evolutionary algorithm that can evolve complete programs in an arbitrary language using a variable-length binary string and is compared to genetic programming.
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Grammatical Evolution by Grammatical Evolution: The Evolution of Grammar and Genetic Code
TLDR
This study examines the possibility of evolving the grammar that Grammatical Evolution uses to specify the construction of a syntactically correct solution and provides evidence to show that the co-evolution of grammar and genetic code with a solution using grammatical evolution is a viable approach.
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Occupancy grid mapping: An empirical evaluation
TLDR
This work analyzes the performance of several established mapping techniques using identical test data to determine which approach to the robotic mapping problem imbues a mobile robot with the greatest ability to create an accurate representation of its operating environment.
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A Less Destructive, Context-Aware Crossover Operator for GP
TLDR
A context-aware crossover operator which operates by identifying all possible contexts for a subtree, and evaluating each of them, and the context that produces the highest fitness is used to create a child which is then passed into the next generation.
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Genetic Code Degeneracy: Implications for Grammatical
TLDR
Results show that genetic diversity is improved as a result of degeneracy in the genetic code for the problem domains addressed here.
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Sensor Technology in Autonomous Vehicles : A review
TLDR
How each of these sensors work, their advantages and disadvantages and how sensor fusion techniques can be utilised to create a more optimum and efficient system for autonomous vehicles are explained.
View on IEEE
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