分布式人工智能与机器学习在多智能体环境中的相遇

BRAC UNIVERSITY

Undergraduate Thesis

Computer-Generated Artificial Life Model:

Algorithm for Hunters Hunting Preys

by

Md. Mahbub-Ul Haque

Surid Imam Khan Sur

Rehnuma Binta Shahriar

Supti Rani Saha

© 2021. Brac University

All rights reserved.

Approval

The thesis titled “Computer-Generated Artificial Life Model:Algorithm for Hunters

Hunting Preys” submitted by

1. Surid Imam Khan Sur (17201117)

2. Rehnuma Binta Shahriar (18101421)

3. Md. Mahbub-Ul Haque (18101428)

4. Supti Rani Saha (18101156)

Of Summer, 2021 has been accepted as satisfactory in partial fulfillment of the

Department of Computer Science and Engineering

Brac University

Co-Supervisor:

(Member)

Tanvir Kaykobad

PhD Student

Head of Department:

(Chairperson)

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

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

Acknowledgement

This project would not have been possible without the help of the Almighty. Also,

we would like to thank Dr. M. Kaykobad for introducing us to the problem.

Table of Contents iv

List of Figures vi

1 Introduction 2

1.1 Flock and Flocking Behavior . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Literature Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.3 Objectives of the Thesis . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.4 Organization of the Thesis . . . . . . . . . . . . . . . . . . . . . . . . 7

2 Literature Review 8

2.1 Flocks, Herds and Schools: A Distributed Behavioral Model . . . . . 8

2.2 Boids With a Fuzzy Way of Thinking . . . . . . . . . . . . . . . . . . 10

2.7 On the Identification of the Convex Hull of a Finite Set of Points in

the Plane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

3 Simulation of behavior of animals 22

3.1 The Idea of the Animals’ Behavior . . . . . . . . . . . . . . . . . . . 22

3.2 Flocking Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

3.2.1 Cohesion Algorithm . . . . . . . . . . . . . . . . . . . . . . . . 23

3.2.2 Separation Algorithm . . . . . . . . . . . . . . . . . . . . . . . 25

3.2.3 Alignment Algorithm . . . . . . . . . . . . . . . . . . . . . . . 27

3.3 The Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

3.4 Details of Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29