Project Overview

In this project, I explored how to incorporate Artificial Intelligence into games. I created a simulated environment where both reactive 'Prey' AI agents and planning-based 'Predator' AI agents interacted, inspired by the rabbits' and fox' behaviours.

Each agent in the environment was designed with customizable properties such as speed, vision range, and other defining characteristics. I integrated two distinct AI techniques into the project to achieve a diverse and engaging experience: Behavior Trees were used to control the foxes. At the same time, Utility AI was employed for rabbits.

The agents were equipped with sophisticated sensors such as vision cones and smelling radii, allowing them to gather crucial data about their surroundings and effectively detect their prey.

Expansion

To expand this project, I would implement evolutionary dynamics within the simulated ecosystem, incorporating weighted properties that can be passed down to future generations of agents and introducing elements of chance like dodging and fleeing to add an element of unpredictability.