The document discusses the current applications of artificial intelligence (AI) in gaming, highlighting its impact on player experience, game performance, and development efficiency. It covers various AI functionalities, including enhancing non-player character (NPC) intelligence, procedural content generation, in-game balancing, and story development, along with future possibilities like cloud gaming and blockchain integration. The document also outlines specific AI algorithms used in game design, such as minimax and neural networks, emphasizing their ability to adapt and improve gaming environments.

1. September 28th, 2022
CURRENT APPLICATIONS OF AI:
GAMING
CSE 604: AI

2. HASNAIN IQBAL SHIRSHO SHAFIQ-US SALEHEEN MD. RAKIB TROFDER
BSSE-1106
TEAM KabbikAgent
BSSE-1125 BSSE-1129

3. INTRODUCTION
01
What is AI in Gaming?

4. AI in gaming refers to excellent game experiences which is more-
1. Responsive
2. Adaptive
3. Challenging
Artificial Intelligence brings revolution in player experience, cost reduction, better
performance in gaming sector.
WHAT IS AI IN GAMING?

5. WHY DOES AI MATTER IN GAMING?
PLAYER
EXPERIENCE
BETTER
PERFORMANCE
COMPATIBILIT
Y
INTERACTIVE
STORY
01 02 03 04

6. Makes it easier for the
user to play
The games become
smarter and more
realistic
Developers make Games
that are Very Human-
Like
BENEFITS OF AI IN GAMING

7. Create New Level
Gaming using
Intelligence
Eliminates the
predictability of the
game
Simplifying the Game
Creation and
Development Process.
BENEFITS OF AI IN GAMING

8. APPLICATIONS
02
Typical applications of AI in games

9. ADDING INTELLIGENCE
TO NON-PLAYING
CHARACTERS

10. GARRY KASPAROV
vs
DEEP BLUE
(1997)

11. ALPHA GO
vs
LEE SEDOL
(2016)
● More complex than
Chess
● Used neural networks
instead of probability
algorithms

12. AI-BASED NPCs
Get Smarter
Imitate Top
Players
Not Pre-
programmed
Less
Predictable

13. AI ENEMY AI COMPANION
AI companions provide friendly faces in
a hostile environment. They assist in
navigation, puzzle-solving, and combat.
They alleviate loneliness.
Well-implemented enemy AI is
characterized by the believability of
opposing NPC movement, how they
converse, behave, and react to any
given situation created by the player.

14. HALO GAME SERIES

15. Smart enough to
retreat and take
cover
Micro-decisions and
short-term strategies
to avoid repetitive
outcome
Previous fight records
used to make the enemy
learn
HALO ENEMY AI

16. GAME LEVEL
GENERATION

17. PROCEDURAL
CONTENT
GENERATION
GENERATE NEW
ENVIRONMENTS
CREATE NEW
ASSETS
DIFFICULTY
ESTIMATION
AI IN GAME-LEVEL GENERATION

18. One of the primary aims of play, aside
from staying alive, building stuff and
acquiring goods, is to explore as many
of the over 18 quintillion randomly
generated planets as you like.
Open world? Try open universe.
NO MAN’S SKY

19. STORY DEVELOPMENT

20. AI IN STORY DEVELOPMENT
PLAYER
EXPERIENCE
MODELING
DATA
MINING
INTERACTIVE
NARRATIVE

21. Every interaction opens up a series
of possible improvements.
These actions are somewhat
randomized by design so the AI
doesn't start to feel predictable.

22. AI DUNGEON
Infinite
Possibilities
Based on
Dungeons & Dragons
Generate New
Adventure

23. Mercury is the closest planet to the Sun and
the smallest one in the Solar System—it’s only
a bit larger than our Moon. The planet’s name
has nothing to do with the liquid metal since it
was named after the Roman messenger

24. IN-GAME BALANCING

25. AI IN IN-GAME BALANCING
PLAYER
EXPERIENCE
MODELING
OPTIMIZATIO
N
TESTING

26. FIFA 22
ULTIMATE MODE
● Team Chemistry
● In-game Events
● Competitiveness

27. IMAGE ENHANCEMENT

28. AI IN IMAGE ENHANCEMENT
DEVELOPING
REALISTIC
GAMING
CHARACTER
CUSTOMIZATION
FEATURES
NOISE
REMOVING
BETTER
VIDEO
QUALITY
HYPER-MOTION

29. ALGORITHMS in GAMES
03
Some defined game-AI algorithms

30. BOARD GAME VIDEO GAME
PATH FINDING -
STEERING BEHAVIORS -
- GAME TREE CALCULATION
- BOARD EVALUATION

31. BOARD GAME
GAME TREE CALCULATION
MINIMAX MONTE-CARLO
TREE SEARCH

32. MINIMAX
In Minimax the two players are
called maximizer and minimizer. The
maximizer tries to get the highest
score possible while the minimizer
tries to do the opposite and get the
lowest score possible.

33. METHODS FOR CALCULATION-
EASING
ALPHA-BETA
PRUNING
NULL MOVE
HEURISTIC
QUIESCENCE
SEARCH
01 02 03

34. ALPHA-BETA PRUNING
Alpha is the best value that the maximizer currently
can guarantee at that level or above.
Beta is the best value that the minimizer currently
can guarantee at that level or above.
WHEN ALPHA >= BETA PRUNE REST OF THE TREE
METHODS FOR CALCULATION-
EASING

35. NULL MOVE HEURISTIC
The null-move heuristic is a heuristic technique
used to enhance the speed of the alpha-beta
pruning algorithm.
Game state is evaluated by assuming one player
“passes” a move.
METHODS FOR CALCULATION-
EASING

36. QUIESCENCE SEARCH
The purpose of this search is to only evaluate
"quiet" positions, or positions where there are no
winning tactical moves to be made.
METHODS FOR CALCULATION-
EASING

37. BOARD GAME
EVALUATION
EVALUATION
FUNCTION
DEVELOPMENT
EVALUATE
USING
GENETIC
APPROACH

38. EVALUATION
FUNCTION
DEVELOPMENT
Estimate the value or goodness of a
position in a game tree.
EVALUATING BOARD

39. GENETIC APPROACH
Finds final evaluation function by mutating
some manual-defined evaluation functions.
EVALUATING BOARD

40. VIDEO GAME
PATH FINDING ALGORITHMS
A* SEARCH BFS/DFS
INFORMED
SEARCH
UNINFORMED
SEARCH

41. A* SEARCH
MINIMIZES PATH COST,
WHICH = COST FROM
SOURCE + HEURISTIC
COST FROM CURRENT
NODE TO DESTINATION

42. VIDEO GAME
STEERING BEHAVIOR
SEEK PATH
FOLLOWING

43. SEEK
The addition of steering
forces to the character
every frame makes it
smoothly adjust its velocity,
avoiding sudden route
changes.

44. PATH FOLLOWING
The path following steering
refers to the character
constantly adjusting its
direction to catch the
target.

45. FINITE STATE MACHINE

46. Artificial neural networks (NNs) are structures akin to human brains that
can learn various features from training data. Given a large set of data,
NNs are capable of modeling very complex real-world and game
scenarios. NNs overcome some of the shortcomings of classic AI
techniques in game agent design. Furthermore, NNs are self-adaptive
and adapt well to game environments that change in real-time.
Advantage => Too smart agent
Disadvantage => Too smart agent
Neural Networks

47. FUTURE OF AI IN GAMING
04
What else can be done?

48. Cloud-Based Gaming
with AI
Cloud gaming is a technology that streams games across the Internet rather than
requiring the user to download and install the game.

49. Voice or Audio
Recognition-Based Games
With voice recognition in gaming, the user can control the gaming gestures,
monitor the controls, and even side-line the role of a controller.

50. Wearable Support
Gaming and VR Gaming
Experiential games like AR, VR and MR, making them more realistic and
progressive towards entertainment.

51. Blockchain-Based
Gaming
Blockchain-based gaming indicates that both, gamers and developers need to
get together on the blockchain platform to play these games

52. Improved Mobile
Gaming Experience
Mobile gaming have been focusing on and developing devices compatible with
high resolution and heavy graphics.

53. CAN an AI develop an AI based game
?

54. THANK YOU
Do you have any questions?

55. REFERENCES
1. https://www.engati.com/blog/ai-in-
gaming#:~:text=Deterministic%20AI%20techniques%20are%20the,understand%2C%20test%2
C%20and%20debug.
2. https://pianalytix.com/role-of-artificial-intelligence-in-gaming/
3. Why Halo's Enemy AI is the Best in Gaming (cbr.com)
4. Red Dead Redemption 2 Fan Uses AI to Create Realistic Photo of Arthur (gamerant.com)
5. No Man's Sky (nomanssky.com)
6. How Artificial Intelligence (AI) Is Used in Game Development (pixelplex.io)