Dynamics Underneath Symbols: A Case Study in Autonomous Agents

TL;DR

This paper investigates the relationship between informational and physical layers in cognition using a simulated agent in a T-maze, revealing complex behaviors when multiple stimuli are presented.

Contribution

It introduces a dynamical systems perspective to study how physical and informational layers interact in autonomous agents, highlighting behaviors under simultaneous stimuli.

Findings

Observed complex fluctuation behaviors in agent choices

Demonstrated interactions between multiple tokens influence decision dynamics

Provided insights into physical-informational layer coupling

Abstract

Our cognition is structuring the informational layer, consisting of perception, anticipation, and action, and it should also be sustained on a physical basis. In this paper, we aim to explore the relationship between the informational layer and the physical layer from a dynamical systems point of view. As an example, the fluctuation of choice is investigated by using a simulated agent. By setting a T-maze, the agent should choose one arm of the maze if a corresponding token is presented. We prepared two types of tokens, corresponding to the left and right arm of the maze. After training the network of the agent to successfully choose the corresponding arm, we presented two tokens simultaneously to the agent and observed its behavior. As a result, we found several behaviors, which are difficult to speculate on from a case in which only a single token is presented to the agent. Detailed analyses and the implications of the model are discussed.