2017 年 8 巻 2 号 p. 36-51
In recent years, accidents and product recalls caused by product failures have become major problems in many industries worldwide. To predict how changes of a product recall system affects safety in the society and to get valuable suggestions to improve product recall systems, we simulated the recall process in society using social simulation model. This research is important because the current product recall systems are not designed by mathematical and predictive approaches such as a computer simulation, but designed by empirical approaches. As a simulation model, we propose Layered Co-evolution Model with Logic Value Typed Genetic Programming (GP). We evaluated the proposed method by using the multi-agent simulation in an artificial society where producer agents and consumer agents both compete and cooperate with each other. This experiment discovered that the producer agents and the consumer agents are able to co-evolve toward a convergence point in Layered Co-evolution Model through the interactions between both types of agents. From the experiment, it is also understood that Logic Value Typed GP, which uses logic values and logic operators, has the advantages over the existing GP method that uses real number values. The Logic Value Typed GP is more stable in the evolutionary process and more efficient in terms of agents' learning process. In addition, we predicted that making the accident-compensation-level stricter decreases the frequency of product accidents in the whole artificial society. This is the result of the producer agents increasing the frequency of product recalls or raising production costs under such a stricter level. This prediction is useful for realizing a safer society.