Artificial Intelligence Based Automatic Generation of Entertaining Gaming Engines

Dr. Zahid HalimFaculty of Computer Science and EngineeringGhulam Ishaq Khan Institute of Engineering Sciences and Technology, Topizahid.halim@giki.edu.pk 19th June 2012

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Layout

Artificial Intelligence

Results of the experiment

Questions

AI

What is not AI and application of AI~ AI

Q/A

Case Study

Results

Nuts and bolts of a predator/prey gaming engine

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

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• Intelligence is the computational part of the ability to achieve goals in the world

• One of the most dumbest thing in world is computer

• Recall the two numbers addition program using int data type

• Artificial intelligence allows computers to• Think like humans• Learn from experience• Recognize patterns in large amounts of complex data • Make complex decisions based on knowledge and

reasoning skills

Artificial Intelligence (AI)

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

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NOT AI• A meter reading algorithm

at petrol pumps• Encyclopedia • SQL query

• TOPIO, humanoid robot can play ping-pong with human

• Speech and Voice Recognition

• Face recognition

AI

AI is notEverything fast is not AI

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines5

• Artificial Neural Networks• Swarm Intelligence• Evolutionary Computation• Pruning Algorithms

:::

(and the list goes on)

AI tools

Automated Game GenerationA Case Study

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines7

Search Space Predator/prey Games

• 14 X 14 grid excluding the

boundary walls.

• Couple of walls at fixed positions

and of size 7 cells 

• There is one player controlled by

the human player.

• There are N (0-20)other pieces of

M (1,2 and 3) types

• Maximum duration 100 game

steps

• Finish game

• Agent dies

• Maximum score is achieved

• Maximum game steps

utilized

•  Movement logic

• No movement

• Clockwise

• Counter clockwise

• Random

• Random direction

•  Collision logic

• no effect

• random relocation to a new

location on the grid

• death.

•  Scoring logic

• +1, -1, 0

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Chromosome Encoding for Genetic Algorithm

Number of predators

Red 0-20

Collision logic

Blue-Green 0-2Green 0-20 Blue-Blue 0-2

Blue 0-20 Blue-Agent 0-2

Movement logicRed 0-4 Agent-Red 0-2Green 0-4 Agent-Green 0-2

Blue 0-4 Agent-Blue 0-2

Collision logic

Red- Red 0-2

Score logic

Red- Red -1,0,+1Red- Green 0-2 Green-Green -1,0,+1Red-Blue 0-2 Blue-Blue -1,0,+1Red- Agent 0-2 Agent-Red -1,0,+1Green-Red 0-2 Agent Green -1,0,+1Green-Green 0-2 Agent-Blue -1,0,+1Green-Blue 0-2 Green-Red -1,0,+1Green-Agent 0-2 Blue-Red -1,0,+1Blue-Red 0-2 Blue-Green -1,0,+1

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

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Entertainment Metrics• Duration of the Game

• Appropriate Level of Challenge

• Diversity

• Usability

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

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Rule Based Controller• The controller looks up, down, left and right. It notes the nearest piece (if

any) in each of the four directions, and then it simply moves one step towards the nearest score increasing piece

• If there are no score increasing piece present it determines its step according to the following priority list

• Move in the direction which is completely empty • If more than one directions are empty move towards the farthest

wall• Move in the direction which contains a score neutral piece• Move in the direction which contains a score decreasing piece• Move in the direction which contains a death causing piece

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

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Neural Network Based Controller• Multi-layer fully feed forward • 6 neurons in the input layer• 5 neurons in the hidden layer • 4 output layer neurons• Sigmoid activation function• Edges weights -5 to +5. ∆xr

∆xg

∆xb

∆yg

∆yb

∆yr NuNd

Nl

Nr

Connection Edges

Connection Edges

Connection Edges

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

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Experimentation Setup• 10 chromosomes are randomly initialized by the GA

• One offspring is created for each chromosome • Duplicating it• Mutating any one of its gene

• Results in 20 chromosomes from which 10 best chosen

• 100 generations

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

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Appropriate level of challenge

Duration of game

Diversity

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

Predators Movement logic Collision logic

(a)

R G B R G B R-R R-G R-B R-A G-R G-G G-B G-A B-R3 17 13 3 0 3 2 1 1 0 0 1 0 2 1

Collision logic Scoring logicB -G B-B B-A A-R A-G A-B R-R G-G B-B A-R A-G A-B G-R B-R B-G

2 2 2 0 0 2 -1 -1 0 -1 0 0 -1 -1 0

Predators Movement logic Collision logic

(b)

R G B R G B R-R R-G R-B R-A G-R G-G G-B G-A B-R0 18 10 0 1 3 2 2 1 1 2 0 0 1 1

Collision logic Scoring logicB -G B-B B-A A-R A-G A-B R-R G-G B-B A-R A-G A-B G-R B-R B-G

1 1 1 1 0 2 0 1 0 1 -1 -1 1 -1 -1

Predators Movement logic Collision logic

(a)

R G B R G B R-R R-G R-B R-A G-R G-G G-B G-A B-R10 0 11 0 0 3 1 2 1 1 0 0 2 0 2

Collision logic Scoring logicB -G B-B B-A A-R A-G A-B R-R G-G B-B A-R A-G A-B G-R B-R B-G

2 2 2 2 0 2 1 1 -1 0 1 -1 -1 1 0

Predators Movement logic Collision logic

(b)

R G B R G B R-R R-G R-B R-A G-R G-G G-B G-A B-R7 7 8 2 4 3 2 0 2 2 0 0 2 1 2

Collision logic Scoring logicB -G B-B B-A A-R A-G A-B R-R G-G B-B A-R A-G A-B G-R B-R B-G

0 0 0 2 0 2 -1 0 0 0 1 1 1 1 0

Predators Movement logic Collision logic

(a)

R G B R G B R-R R-G R-B R-A G-R G-G G-B G-A B-R0 10 0 2 4 2 0 1 2 1 2 0 2 0 1

Collision logic Scoring logicB -G B-B B-A A-R A-G A-B R-R G-G B-B A-R A-G A-B G-R B-R B-G

1 0 2 1 0 2 -1 0 -1 1 0 -1 0 -1 -1

Predators Movement logic Collision logic

(b)

R G B R G B R-R R-G R-B R-A G-R G-G G-B G-A B-R0 17 0 4 4 4 1 2 0 0 0 1 2 2 1

Collision logic Scoring logicB -G B-B B-A A-R A-G A-B R-R G-G B-B A-R A-G A-B G-R B-R B-G

1 1 2 1 0 2 -1 -1 0 0 -1 -1 -1 1 0

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Usability

Combined Fitness

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

Predators Movement logic Collision logic

(a)

R G B R G B R-R R-G R-B R-A G-R G-G G-B G-A B-R20 18 19 1 2 2 2 0 0 2 2 1 2 0 2

Collision logic Scoring logicB -G B-B B-A A-R A-G A-B R-R G-G B-B A-R A-G A-B G-R B-R B-G

2 2 0 2 0 2 1 -1 0 1 0 0 -1 0 0

Predators Movement logic Collision logic

(b)

R G B R G B R-R R-G R-B R-A G-R G-G G-B G-A B-R19 20 20 4 4 2 2 0 2 2 2 2 0 2 2

Collision logic Scoring logicB -G B-B B-A A-R A-G A-B R-R G-G B-B A-R A-G A-B G-R B-R B-G

2 0 2 2 0 2 -1 -1 1 -1 1 1 0 -1 -1

Predators Movement logic Collision logic

(a)

R G B R G B R-R R-G R-B R-A G-R G-G G-B G-A B-R15 8 3 1 1 0 1 2 0 0 1 0 1 2 0

Collision logic Scoring logicB -G B-B B-A A-R A-G A-B R-R G-G B-B A-R A-G A-B G-R B-R B-G

2 2 0 0 0 0 1 1 -1 -1 -1 1 -1 -1 -1

Predators Movement logic Collision logic

(b)

R G B R G B R-R R-G R-B R-A G-R G-G G-B G-A B-R11 20 3 2 4 2 2 2 0 2 2 2 0 1 1

Collision logic Scoring logicB -G B-B B-A A-R A-G A-B R-R G-G B-B A-R A-G A-B G-R B-R B-G

1 1 2 0 0 2 0 1 1 -1 1 0 -1 0 1

1 3,34 54 56 66 …. !!!

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Controller Learning Ability

Diversity-RB

Duration-RB

Challenge-RB

Usability-RB

Diversity-ANN

Duration-ANN

Challenge-ANN

Usability-ANN

Combined-RB

Combined-ANN

Random

0 200 400 600 800 1000 1200

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

•User Survey• 10 subjects• Conducted in two different sets on different days

• Rule based controller • ANN based controller• Each individual was given 6 games• Play 2 times

Rand

om

Duratio

n

Challe

nge

Diversi

ty

Usabilit

y

Combin

ed Fit

ness

048

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Rule Based Con-trollerANN Based Con-troller

Duration4%

Challenge32%

Usability24%

Combined Fitness

40%

Human User Survey ANN Based Controller

Duration12%

Chal-lenge24%

Usability18%

Com-bined

Fitness47%

Human User Survey Rule Based Controller

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

Questions

This presentation is uploaded at http://ming.org.pk/zahid.htm

Thank you for your patience

Bibliography• Halim, Zahid, A. Rauf Baig, and Hasan Mujtaba. "Measuring entertainment and automatic generation of entertaining

games." International Journal of Information Technology, Communications and Convergence 1.1 (2010): 92-107.

• Halim, Zahid, A. Rauf Baig, and Mujtaba Hasan. "Evolutionary Search For Entertainment In Computer Games." Intelligent Automation & Soft Computing 18.1 (2012): 33-47.

• Halim, Zahid, and A. Raif Baig. "Evolutionary Algorithms towards Generating Entertaining Games." Next Generation Data Technologies for Collective Computational Intelligence. Springer Berlin Heidelberg, 2011. 383-413.

• J.Schmidhuber, ”Developmental robotics, optimal artificial curiosity, creativity, music, and the fine arts”, Connection Science, vol. 18, pp.173–187, 2006

• N. Esposito, “A Short and Simple Definition of What a Videogame Is”, in proceedings of Digital Games Research Association (DiGRA), Vancouver, Canada, 16-20 June, 2005

• J.Smed and H.Hakonen, "Towards a Definition of a Computer Game", Technical Report, Computer Games Research Group, Department of Information Technology, University of Turku, Finland, 2005

• http://www.glasbergen.com/computer-cartoons/

• http://www-formal.stanford.edu/jmc/whatisai/node1.html

• G. N. Yannakakis , J. Hallam, ”Towards Optimizing Entertainment In Computer Games”, Applied Artificial Intelligence”, v.21 n.10, p.933-971, November 2007

• http://www.easy-marketing-strategies.com/writing-a-case-study.html

• http://www.123rf.com/photo_9926111_confused-cartoon-guy.html

Artificial Intelligence based Automatic generation of Entertaining Gaming Engines

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