Patches As Agents

Abstract

StarLogo Nova is a powerful agent-based game and simulation programming environment designed for classroom learning. This modeling tool allows students to apply their creativity and replicate real-world phenomena through game-like coding and scientific knowledge. However, the current agent-to-environment interaction is limited, with the environment(terrain) possibly affected by the agent’s action, but unable to initiate actions autonomously. This thesis proposes an innovative approach to Star- Logo Nova by transforming the static environment into a dynamic structure made of thousands of patch agents. In this new framework, the traditional static terrain is now composed of a collection of independent patch agents, each with its own behaviors and traits. This transformation enables the patch agents to actively interact with each other and the surrounding agents, expanding potential for a more complex and responsive simulation.