Using General Collective Intelligence to Optimize the Process of Evolutionary Optimization

In the study of logic, state spaces have been used to define semantic representations of theories for the purpose of abstract problem-solving. This paper explores the use of a variety of state space (a functional state space) defined through the emerging technique of Human-Centric Functional Modeling, in a thought experiment to model all information required in the process of problem-solving using evolutionary computing, and all the information required to index evolutionary computing solutions and the problems they are meant to solve, so those problems and solutions can be uniquely identified and compared, in order to move towards automation of the process of evolving such evolutionary computing solutions by applying such solutions to the design of the solutions themselves.