Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Random recombination in evolutionary algorithms can be counterproductive in systems that evolve increasing modularity, because such operators do not preserve community structures during their development. Partly because of this, methods have been proposed that derandomize recombination by placing potential crossover locations under evolutionary control. Since crossover is likely to be particularly useful when genetic material that generates incipient phenotype modules is recombined, there may be an advantage to seeking such modularity directly in the phenotype and probabilistically focusing recombination at such "hotspot" locations. Here  show that such phenotypically-aware crossover operators can outcompete random or evolved crossover points as the size of the system being evolved grows. As this crossover operator can be vied as epigenetic, and as epigenetic processes seem to be common in biological systems, other such epigenetic mechanisms may further improve future evolutionary algorithms.
['Ari Larson', 'Anton Bernatskiy', 'Collin K. Cappelle', 'Kenneth R. Livingston', 'Nicholas Livingston', 'John H. Long', 'Jodi A. Schwarz', 'Marc L. Smith', 'Josh C. Bongard']
I am writing a research paper on a idea Recombination Hotspots Promote the Evolvability of Modular Systems
[{"from": "human", "value": "I am writing a research paper on a idea Recombination Hotspots Promote the Evolvability of Modular Systems"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Random recombination in evolutionary algorithms can be counterproductive in systems that evolve increasing modularity, because such operators do not preserve community structures during their development. Partly because of this, methods have been proposed that derandomize recombination by placing potential crossover locations under evolutionary control. Since crossover is likely to be particularly useful when genetic material that generates incipient phenotype modules is recombined, there may be an advantage to seeking such modularity directly in the phenotype and probabilistically focusing recombination at such \"hotspot\" locations. Here  show that such phenotypically-aware crossover operators can outcompete random or evolved crossover points as the size of the system being evolved grows. As this crossover operator can be vied as epigenetic, and as epigenetic processes seem to be common in biological systems, other such epigenetic mechanisms may further improve future evolutionary algorithms."}]