ARTIFICIAL INTELLIGENCE IN COMPUTER GAMES

(GATE-561)

 

Game Technologies Program, Department of Modeling and Simulation

Informatics Institute

Middle East Technical University

 

Fall 2009

 

 

Dr.Çağatay ÜNDEĞER

 

Instructor

Middle East Technical University, GameTechnologies

Bilkent University, Computer Engineering

 

&

 

General Manager

SimBT Inc.

 

Room : II-206

e-mail : cagatay@undeger.com

web-site : www.cs.bilkent.edu.tr/~cagatay

 

 

1.      Objective & Scope

 

The course presents the theoretical basics of artificial intelligence (AI) and their practical application to behavior modeling in game development.

 

After a brief introduction to game aspects, AI and role of AI in games, the first part of the lecture will introduce frequently used AI architectures, which can be used for designing AI engines in games; and the second part will cover basic decision taking, search and planning techniques towards detailed reasoning of a game entity. Next part will deal with group behavior which makes an individual entity take decisions considering a group of entity in coordination and cooperation. Finally, the last part will cover high and low level script programming issues, which is very commonly used in games.

 

In the course, students will be given term papers to be read, which will be summarized and presented in the class. Additionally, there will be survey, design and/or implementation assignments to be presented/demonstrated in the class. Finally, the students will develop and present individual projects related with entity behavior modeling in games.

 

1.      Course Outline

 

•         Introduction to Course

•         Introduction to Common Game Components

–        Environment

–        Scenario

–        Perception

–        Behaviour

–        Physics

–        Body Movement and Animation

–        Visual Effects

–        Sound Effects

•         Introduction To Artificial Intelligence (AI)

–        Description of AI

–        History of AI

–        Behavior and Agent Types

–        Properties of Environments

–        Problem Solving Strategies

–        Common Search Strategies

•         Common AI Architectures

–        Entities, Attributes and Relations

–        Tasks, Actions, States and Events

–        Finite-State Machines

–        Hierarchical Finite-State-Machines

–        A Sample AI Architecture

•         Reactive Behavior Modeling

–        Introduction to Reactive Behaviors

–        Fuzzy Logic

–        Neural Networks

–        Decision Trees

–        Instance-Based Learning

•         Deliberative Behavior Modeling

–        Introduction to Deliberative Behaviors

–        Game Trees

–        Production Systems

–        Path Planning

1.      Environment Modeling

1.      Grid-Based Models

2.      Polygonal Models

2.      Off-line Path Planning

1.      Uninformed Search

1.      Breadth First Search

2.      Depth First Search

3.      Iterative Deepening Search

4.      Bidirectional Search

5.      Dijkstra’s Algorithm

2.      Informed (Heuristic) Search

1.      A*

2.      A* Derivations

3.      Incremental Search

1.      D*

2.      D*Lite

4.      Random Search

1.      Hill-Climbing

2.      Simulated Annealing

3.      Random Trees

4.      Probabilistic Roadmaps

5.      Genetic Algorithms

5.      Hierarchical Planning Techniques

6.      Path Smoothing Techniques

3.      On-line (Real-time) Path Planning

1.      RTA*

2.      MTS

3.      MTES

•         Group Behaviors        

–        Formations

–        Flocking

–        Multi-Agent Pursuit

•         Script Programming

–        Low Level Scripts

–        High Level Scripts

•         Knowledge Representation

–        Semantic Networks

–        Frames

•         Time Management

–        Discrete Time Management

–        Continuous Time Management

–        Discrete Event Simulations

•         Paper/Assignment Presentations

•         Project Presentations

 

2.      Course Requirements

 

The students are expected to develop a small-scale AI project individually or with a group of two. The project topics will be selected from a list of topics provided by the instructor (additional topics can be proposed). Implementation will be done in C++ preferably with Visual Studio (V6.0 or .NET) or Borland C++ Builder (V6.0 or 2009).

 

3.      Assessment Method

 

A project will be developed including:

            Project Documents (Final Report, Source Code, Executables)            30%

            Project Presentation and Demonstration                                              20%

Assignments:

Implementation Assignments                                                               25%

Paper Reading/Presentation Assignments                                            25%

 

4.      List of Project Topics

 

a.       War Craft like strategy game with attack and defense behavior of two opposing forces.

                                                   i.      Number of students: preferably 2

                                                 ii.      Environment: A war craft like grid world environment with obstacles.

                                                iii.      User control: Locate defense forces and define their initial defense mission by orders. Locate attack forces and define their initial attack mission by orders.

                                               iv.      Automated entities: Both defense and attack forces

                                                 v.      Behavior: Defense forces defend a region (a small town etc.) and try to prevent attack forces to enter their region autonomously. Attack forces try to kill defense forces and get protected area autonomously. User should not need to order the entities all the time. Entities should have enough intelligence to decide and navigate appropriately. For instance if attack is from north, most of them should go to north, and little should stay south (but not all).

                                               vi.      Visualisation: Looking environment from the top view.

 

b.      Hide and escape behavior of a group of tanks against a helicopter attack.

                                                   i.      Number of students: 1-2

                                                 ii.      Environment: A grid world environment with obstacles and mountains preventing line of sight.

                                                iii.      User Controlled Entities: A simple helicopter with a formulized sensor range (depending on the target velocity) and limited with field of view.

                                               iv.      Automated entities: One or more tanks having a predefined scenario (navigation corridor/path). Tanks have larger fixed sensor ranges and they know that helicopters have lower range, but does not know exact the range value. They just have an estimate.

                                                 v.      Behavior: A group of tanks moving through the navigation corridor/paths that are predefined in the scenario, but they can deviate from their path if they see a helicopter. Possible deviations are as follows:

1.      If no helicopter is seen, go through the path.

2.      If a helicopter is seen that is far and/or not going directly towards you, estimate that it hasn’t seen you and perform a hide behavior which may be:

1.      Slow down or stop in order to prevent detection

2.      Hide and stop behind a mountain area

3.      Determine a new path to target location near to original path far from the helicopter area and continue movement

3.      If helicopter is near and going directly towards you

1.      Split the group and escape randomly far from the helicopter until you feel safe.

4.      If helicopter is invisible again, resume mission and go to target point.

                                               vi.      Visualisation: Looking terrain from the top view and just see the tanks detected by the sensors.

 

c.       Follow and help behavior:

                                                   i.      Number of students: preferably 2

                                                 ii.      Environment: polygonal (triangulated) navigation areas with holes/gaps.

                                                iii.      User Controlled Entities: A 3d main character controlled by the user which can move freely in neighboring areas and jump between the areas having gaps in between.

                                               iv.      Automated entities: A 3d helper character. If 2 students are in the project, there will be some attack forces/aliens.

                                                 v.      Behavior: A 3d helper character following the main character in the environment. If 2 students are in the project, helper character will be defending the main character against the attacks with guns (sword and/or pistol, etc.). Some entities will be attacking entities against main and helper characters.

                                               vi.      Visualisation: 3d environment

 

d.      Dog fight:

                                                   i.      Number of students: 1

                                                 ii.      Environment: : A grid world environment with mountains.

                                                iii.      User Controlled Entities: One of the aircrafts may be controlled by the user.

                                               iv.      Automated entities: A group of opposing aircrafts

                                                 v.      Behavior: Two groups of aircrafts are given a mission path that are intersecting each other. When they come close two each other they will attack each other until one group is terminated and later on the winning group will continue on its predefined path. One of the aircrafts may be controlled by the user.

                                               vi.      Visualisation: may be a 3D view

 

e.       Traffic simulation:

                                                   i.      Number of students: 1-2

                                                 ii.      Environment: a connected graph with intersections and roads having one or two way directions/lanes and one or multiple lanes within one direction. The number of lanes may be changing on a single road in different regions.

                                                iii.      User Controlled Entities: None or one car may be controlled by the user

                                               iv.      Automated entities: Traffic/cars in the environment.

                                                 v.      Behavior: Traffic will be fully automated with cars located around randomly.

                                               vi.      Visualisation: Top view

 

f.        Two body (soldier) defense supported forward movement:

                                                   i.      Number of students: 1-2

                                                 ii.      Environment:  A grid world environment with obstacles

                                                iii.      User Controlled Entities: None

                                               iv.      Automated entities: One of more two soldier groups attacking a defended area with opposing forces.

                                                 v.      Behavior: Defense forces will be still and firing the arrack forces. If they are under fire, they fire less frequently and less correctly, but if they are not under fire, they fire more frequently and more correctly. Attack forces are in two body groups (in each group there are two soldiers). They are moving forward on their path (a corridor with a predefined with). But movement of each soldier is one by one. One will be hiding behind and obstacle and protecting the other; and the other will be moving forward (may be firing meanwhile). After the moving one hides behind an obstacle, the roles of soldiers are exchanged.

                                               vi.      Visualisation: Top view

 

g.       Firing with bombs and missiles against a moving target:

                                                   i.      Number of students: 1

                                                 ii.      Environment: An environment with some obstacles

                                                iii.      User Controlled Entities: Escaping entity is controlled by the user.

                                               iv.      Automated entities: Attacking entity

                                                 v.      Behavior: Attacking entity will follow and try to kill the other moving entity. Attacking entity should estimate the firing direction against an unknown estimated escape movement.

                                               vi.      Visualisation: May possibly be top view

 

h.       A backgammon like game (or something similar):

                                                   i.      Number of students: 1

                                                 ii.      User Controlled Entities: One side

                                                iii.      Automated entities: The other side

                                               iv.      Behavior: The other side will play autonomously, but backgammon rules will be significantly differentiated (no ready source code should be used so the game should be something unknown).

 

i.         Intelligent sensing while moving:

                                                   i.      Number of students: 1

                                                 ii.      Environment: A grid or polygonal based city like environment with obstacles preventing line of sight

                                                iii.      User Controlled Entities: None or moving entity may be controlled by the user

                                               iv.      Automated entities: A moving entity and some entities in the city firing the moving one with some random delays (they will be fixed or moving with a predefined scenario)

                                                 v.      Behavior: Moving entity will move on a predefined fixed navigation path and if see someone, it will shoot. Meanwhile moving it should maximize its perception in order not to be killed. Therefore it should:

1.      Kill anyone around

2.      Look around to maximize vision

3.      Look at sides while passing an obstacle corner to maximize vision

4.      Look behind in order to detect someone pop up behind

5.      Look at the direction that a sound (firing) is coming

6.      Look at more dangerous ones with higher priority (but don’t forget the others)

7.      Track moving entities to keep seeing it

                                               vi.      Visualisation: Top view

 

j.        Bird behavior:

                                                   i.      Number of students: 1

                                                 ii.      Environment: A grid or polygonal base environment with mountains and trees

                                                iii.      User Controlled Entities: A man

                                               iv.      Automated entities: Birds

                                                 v.      Behavior: Birds are flying around randomly or within a flock. Sometimes they stay on top of a tree. If man is closer to them, they escape, avoid and go somewhere or fly to another tree.

                                               vi.      Visualisation: Any

 

k.      A generic AI engine:

                                                   i.      Number of students: 1-2

 

5.      References

 

[1] “Artificial Intelligence and Soft Computing: Behavioral and Cognitive Modeling of the Human Brain”, Amit Konar, CRC Press, 2000

 

[2] “Game Programming Gems”, Mark DeLoura, Charles River Media, 2000

 

[3] “Artificial Intelligence: A Modern Approach”, Stuart Russel and Peter Norvig, Prentice Hall, 1995

 

[4] “Machine Learning”, Tom M. Mitchell, 1997

 

6.      Course Materials

 

1)      Course Introduction

2)      Introduction to Game Components

3)      Introduction to AI

4)      Common Architectures

5)      Reactive Behavior Modeling: FuzzyLogic

6)      Reactive Behavior Modeling: Neural Networks

7)      Reactive Behavior Modeling: Decision Trees

8)      Deliberative Behavior Modeling: Introduction to Path Planning

9)      Deliberative Behavior Modeling: Off-line Path Planning

10)  Deliberative Behavior Modeling: On-line Path Planning