Emergence of Cross-Generational Migration Behavior in Multiagent Simulation

Abstract

We describe an artificial ecosystem consisting of five areas and evolving artificial creatures (called agents). The ecosystem is for an analysis of cross-generational migrations of the monarch butterfly. The monarch butterfly is famous for its migration. We report simulations on the emergence of migration behavior pertaining to the monarch butterfly. The area has two kinds of environmental changes: long-term and short-term changes. We focus on temperature as an environmental parameter. Under long-term change, temperature is gradually rising, and under short-term change temperature changes periodically as same as seasonal change. We put agents on the areas. The agent has two genetic components: an environmental adaptation scale and an action decision table. These components represent the physical features of the agent and select an action on the basis of sensory information, respectively. The agent also has a temperature sensor that functions with its environmental adaptation scale. It enables the agent to adapt dynamic temperature changes and to evolve to obtain optimal behaviors. With the ecosystem, we conduct one experiment. The result was that we observed that the range of migration expanded as the temperature rose. Also, we report the result of migration patterns obtained by the agents. These results show that the biology of the monarch butterfly is well modeled by the ecosystem and our evolutionary method.