Introduction of Consciousness Model to Agents and Simulation of Individuality Acquisition in Appetite

Abstract

The purpose of this study is to implement a human consciousness model based on Jung psychology as a learning model of a machine learning agent so that the agent can acquire individual character from the result of its own behavior. While existing AI agents have been given characteristics by incorporating human-like behaviors and reactions according to the environment, this method make it possible to realize a variety of AI agents without human labor. The consciousness model has a part that corresponds to the instinct including the three major human desires, and this is one of the behavioral factors of the agent. In this paper, we focus only on "appetite" and use reinforcement learning to learn behaviors that satisfy appetite. The parameters, learning environment, and data exchanged to satisfy appetite are implemented based on Jung's typology. Multiple agents are prepared by changing the initial parameters, and learning is performed for each. Each trained agent is activated in the production environment. The behavior and accumulated data of each agent are compared and evaluated with the results of manual operation by humans. As a result, we verify whether we can obtain a difference that can be said to be the individual character of the agent.