An investigation into Cellular Automata: The Self-Modifying Instruction-Based Approach
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In this thesis we investigate a method for genotype representation in cellularautomata. This method is inspired from gene regulation process in biology andis called self-modification. This is then combined with instruction-based approachto form SMIBA.In order to test this new method, SMIBA together with IBA and TT wastested on a number of problems relevant in artificial life. This firstly, being theproblems of replication and of development, which are seen as vital for selfreplicatingmachines. Secondly, these two problems of replication and developmentare then combined into a new novel problem, which is then subsequentlyused to test the different methods.SMIBA was seen to perform well, in comparison to the other methods, onall problems tested. SMIBA and IBA were also shown to scale exceptionally wellwhen incrementing maximum possible states of the CA, often even performingbetter. Further properties in SMIBA of delayed development and hierarchy werealso identified.