Security policies are becoming more sophisticated. Operational forces will often be faced with making tricky risk decisions and policies must be flexible enough to allow appropriate actions to be facilitated. Access requests are no longer simple subject access object matters. There is often a great deal of context to be taken into account. Most security work is couched in terms of risk manageme...

A novel Grammatical Genetic Algorithm, the meta-Grammar Genetic Algorithm (mGGA) is presented. The mGGA borrows a grammatical representation and the ideas of modularity and reuse from Genetic Programming, and in particular an evolvable grammar representation from Grammatical Evolution by Grammatical Evolution. We demonstrate its application to a number of benchmark problems where significant pe...

Grammatical Evolution is an evolutionary algorithm that can evolve complete programs using a Backus Naur form grammar as a plug-in component to describe the output language. An important issue of Grammatical Evolution, and evolutionary computation in general, is the difficulty in dealing with deceptive problems and avoid premature convergence to local optima. Novelty search is a recent techniqu...

We outline the Grammatical Evolution algorithm before an exposition of some of the more recent research and developments in this form of grammar-based Genetic Programming. Some potential avenues for further exploration

This proof of concept study examines the possibility of specifying the construction of programs using Differential Evolution, and represents a new form of grammar-based genetic programming, Grammatical Differential Evolution (GDE). In GDE each individual member of the population represents a specific choice of program construction rules, where these rules are specified using a Backus-Naur Form ...

We present a work in progress describing attribute grammar approaches to Grammatical Evolution, which allow us to encode context-sensitive and semantic information. Performance of the different grammars adopted are directly compared with a more traditional GA representation on five instances of an NP-hard knapsack problem. The results presented are encouraging, demonstrating that Grammatical Ev...

We present Constituent Grammatical Evolution (CGE), a new evolutionary automatic programming algorithm that extends the standard Grammatical Evolution algorithm by incorporating the concepts of constituent genes and conditional behaviour-switching. CGE builds from elementary and more complex building blocks a control program which dictates the behaviour of an agent and it is applicable to the c...