Intelligent process control utilising symbiotic memetic neuro-evolution
Av.E. Conradie, Risto P Miikkulainen, Chris Aldrich · 2003
A novel reinforcement learning algorithm, called symbiotic memetic neuro-evolution (SMNE), is presented for neurocontroller development in nonlinear processes. A highly nonlinear bioreactor process is used in a learning efficiency case study. The use of implicit fitness sharing maintains genetic diversity and induces niching pressure, which enhances the synergetic effect between the global search (symbiotic evolutionary algorithm) and the local search (particle swarm optimisation). SMNE's synergetic effect accelerates learning, which translates to greater economic return for the process industries.