An artificial life approach for investigating the emergence of a Theory of Mind based on a functional model of the brain

In social interactions human can behave cooperatively by estimating the intention of others and predicting their behavior. Understanding of others as having intentional states such as beliefs and desires is called Theory of Mind (ToM). This paper proposes a computational framework based on a Functional Parts Combination model (FPC model) for investigating the emergence of a ToM through adaptation in both evolutionary and individual-learning time scales. The FPC model is based on the neuroscientific fact that each cerebral cortical area has a different role and is selectively activated depending on the task. It consists of a set of functional parts and activation signals specifying selectively activated patterns. As a first step, this paper reports on the computer simulations which focused on the learning of the activation signals using a hunter task as a task to be solved by the agents. The simulation demonstrated a scenario for bootstrapping ToM as the emergence of the partial-networks of functional parts in the brain model based on the interactions between the levels of ToM.