Human based genetic algorithm

A new class of genetic algorithms (GA) is presented, based on the idea of outsourcing, which has the ability to address complex problems for which it is hard, not only to evaluate individuals, but to find a good representation for them.

Abstract

A new class of genetic algorithms (GA) is presented. It is based on the idea of outsourcing, a popular trend in business. In a human based genetic algorithm (HBGA), all primary genetic operators are outsourced, i.e. delegated to external human agents. A totally outsourced genetic algorithm uses both human evaluation and the human ability of innovation. It is a multi-agent environment and the mediator of communication between multiple heterogenous agents. The advantage of this approach is its ability to address complex problems for which it is hard, not only to evaluate individuals, but to find a good representation for them. These qualities allow HBGA to process flows of information without knowledge of its particular structure and representation. The suggested conceptual approach can also be used as a general model and a way of thinking about different kinds of genetic algorithms.