Computer-generated artificial life model: algorithm for hunters hunting preys

Abstract

This thesis simulates the behavior of predators and preys observed between a pack of wolves and a deer herd during a hunting scenario. We use the Boids flocking algorithm, an artificial life model developed by Craig Reynolds to simulate the deer herd. We have also enriched the existing algorithm to help flocks recognize their surroundings, like their neighbors and predators, and react accordingly. The pack of wolves has a leader, and they coordinate as a group isolating a deer from the herd and then capturing it. To implement the predator’s behavior and intelligence, we have developed some algorithms applying their hunting procedure. A part of the research is to explore simple rules that the wolves can follow to achieve their hunting goals. We have also worked on the concept of the Convex Hull algorithm, that can help the predators define their attack positions. Interruptions in the hunting environment between prey and predators that affects the actions of preys and predators have also been studied. In this experiment, actions by the prey and predators are compared in terms of realism.