KEYNOTE“The Future of AI, Game, andComputer Graphics”
Youichiro Miyake
y.m.4160@gmail.com
twitter: @miyayou
http://www.facebook.com/youichiro.miyake

Thanks & Self-Introduction• Welcome to Japan• Thanks for Prof. Ruck Thawonmas• me2004-20112011-Present

AI Programmer (FROM SOFTWARE)
Lead AI Researcher (SQUARE-ENIX)

2007-Present Chairman of IGDA JAPAN SIG-AI
2008-Present Research committee of DiGRA JAPANWorks (2006-2012)
Chrome Hounds (2006)
Demon’s Souls (2009)
PokaPoka Airu Village (2011)
Armored Core V (2012)
Game Titles (AI technical Works)
Books

Recent & Current Status of Game AI
in Game Industry
Number of Game AI Techniques

In these 10 years, field of game AI
has been evolving and expanding.

This rapid changing makes a gap
between academic AI research and
AI development in Game Industry.

Time
1980

1990

2000

2010

But game developers had not passed
their research themes to academic
researchers enough.

Game AI Industry Conference/Community
GDC AI Summit(Game Developer’s
Conference)
http://www.gdconf.com/

Game AI Academic Conference/Community

AIIDE(AI and Interactive
Digital Entertainment )http://www.aiide.org

Paris Game AI Conference
http://gameaiconf.com/

IEEE CIG(IEEE Computational
Intelligence and Games )http://www.ieee-cig.org/

AI Game Dev.COM

IEEE CIS(IEEE Computational
Intelligence Society )http://aigamedev.com/

http://www.ieee-cis.org/

AI Game Programmers Guild
http://www.gameai.com/

The Goal of Keynote
Knowledge(Seeds)Game
Industry

AcademicResearch Themes(Seeds)The Goal of Keynote is introducing many AI research themes ingame industry (I!) to academic researchers (you!) .

AI in Game World
Game Mechanism

Game World(= Environment = Game Stage = Level Design)

AI Character(=NPC)

AI in Game World
Game Mechanism

Meta AI

Game World
Techniques(= Environment = Game Stage =Procedural
Level Design)(Auto-generation, Auto-Control)

AI Character(=NPC)
Character AI(Brain)CHARACTER AI

Life is in the World

http://www.123rf.com/photo_8100542_underwater-photo-of-a-hard-coral-reef.html http://www.gatag.net/04/12/2010/190000.html
http://www.123rf.com/photo_10039937_foggy-forest-at-the-morning-at-autumn.html http://www.flickr.com/photos/rotrauds-kleine-welt/346698184/

Life is in Real World

Real World

Human

Human lives in Real World.

Life is in Real World

Real World
Sensor &Recognition

actionHuman

Human lives in Real World.
Human and Environment interact each other.

AI is in the Game World

AI is in Game World

Game World(= Environment = Game Stage = Level Design)

AI Character(=NPC)

AI lives in Game World.

AI is in Game World

Game WorldAI Character

AI lives in Game World.
AI and Environment interact each other.

AI is in Game World

Game World
Sensor &Recognition

actionAI Character

AI lives in Game World.
AI and Environment interact each other.

AI is in Game World
Information Flow

Game World
Sensor &Recognition

actionAI Character

It makes “Information Flow” between AI and Environment.

C4 Architecture

MIT Media Lab.
Synthetic Characters Group
Researching Virtual Pet in Digital World.

D. Isla, R. Burke, M. Downie, B. Blumberg (2001).,“A Layered Brain Architecture for Synthetic Creatures”, http://characters.media.mit.edu/Papers/ijcai01.pdf

Halo Agent Architecture







Genre：SciFi-FPS
Developer： BUNGIE Studio
Publisher : Microsoft
Hardware: Xbox, Windows, Mac
Year： 2002
Jaime Griesemer(GDC 2002),The Illusion of Intelligence: The Integration of AI and Level Design in Halo
http://www.bungie.net/Inside/publications.aspx

F.E.A.R Agent ArchitectureWorld
Sensors
WorkingMemoryTargeting
Planner
Navigation







Genre：Horror FPS
Developer： Monolith Production
Publisher : SIERRA
Hardware: Windows
Year： 2004

Animation /Movement

Weapons

World

Agent Architecture Considerations for Real-Time Planning in Games (AIIDE 2005)
http://web.media.mit.edu/~jorkin/AIIDE05_Orkin_Planning.ppt

Blackboard

Killzone 2 Architecture







Genre： FPS
Developer： Guerrilla Games
Publisher : SCE
Hardware: PlayStation 3
Year：
Year 2009
Based on: Alex Champandard, Tim Verweij, Remco Straatman, "Killzone 2 Multiplayer Bots",
http://files.aigamedev.com/coverage/GAIC09_Killzone2Bots_StraatmanChampandard.pdf

Demo

Halo AI Retrospective: 8 Years of Work on 30 Seconds of Fun
Author: Damian Isla (AI Engineering Lead)
http://www.bungie.net/Inside/publications.aspx

Agent Architecture
AI

Recognition(Knowledge
Making)Decision
MakingMotionMakingMemorySensorEffecter

Game World

Agent Architecture
AI

Recognitio

Decision
MakingMotionMakingMemorySensorEffecter

Game World

Agent Architecture
AI

Recognitio

Decision
MakingMotionMakingMemorySensorEffector

Game World
Information FlowCharacter AI Research themes(1) Agent Architecture (Framework)(2) Sensor(3) Recognition(4) Memory(5) Decision Making(6) Motion Making( )…

Character AI Research themes(1) Agent Architecture (Framework)(2) Sensor(3) Recognition(4) Memory(5) Decision Making(6) Motion Making( )…

Character AI Research themes(1) Agent Architecture (Framework)(2) Sensor(3) Recognition
Knowledge Making(4) Memory(5) Decision Making(6) Motion Making( )…

(2) Sensor

In many cases, Visual Sensor is implemented as ray-casting model.

(2) Sensor

In many cases, Hearing Sensor is implemented as volume model.
土田善紀、細江一博[CEDEC]5.1ch時代の3D音源・遮蔽・そしてその配置 ～OpenALでは何も出来ない～
http://cedil.cesa.or.jp/session/detail/376

Knowledge Representation
WORLD
AI

Can AI recognize sufficiently the world by his sensors ? No.

Knowledge
Representation
（KR）

WORLD

AI

Information to help AI recognize the World (Object/Fact/Space)＝ Knowledge Representation(KR)31Knowledge Representation (Example: F.E.A.R.(2004))
Working Memory Fact (WMF)

In F.E.A.R.

Character, Object, Mission, Fact, Path, Node, Desire is presented as Unified Form “WMF”
WMF
Place
Direction
Stimulus
ObjectDesireTime

Place(Value, Confidence)
Direction (Value, Confidence)
Stimulus (Value, Confidence)
Object (Value, Confidence)
Desire (Value, Confidence)
Time(Value, Confidence)

16 Field

SECRET

Value
Confidence

Oct.8, 2011

Jeff Orkin, "Three States and a Plan: The A.I. Of F.E.A.R(GDC2006)(Document,PPT,Movie)",2006
http://www.jorkin.com/gdc2006_orkin_jeff_fear.zip© 2011SQUARE
ENIX CO., LTD. All rights
reserved

32

WMF Stacks
Facts AI recognized are stacked in Working Memory as WMFs in each field.

CharacterObjectFact

MissionDesirePathUsing WMF Stacks
Facts AI recognized are stacked in Working Memory as WMFs in each field.
By using WMF stack, AI can estimate some knowledge of the future.

I saw Character A in (60,60) at 10 sec ago.
I saw Character A in (80,40) at 30 sec ago.
I saw Character A in (100,20) at 50 sec ago.
Y
Character

?

60

80

100

X

AI can estimate the character A position in the future.

Knowledge Representation(KR)How many kinds of KR are there ?

Number of how AI should recognize a fact.

“KR”s is the base to make high intelligenceVariation of Knowledge Representation
Dependency Graph

Semantic Network

Rule-based Representation

Enemy Representation

WMF

Army

Steel

Training House

mine

man

tree

World Representation

Griesemer,J, "The Illusion of Intelligence: The Integration of AI and Level Design in Halo", 2002
http://www.bungie.net/images/Inside/publications/presentations/publicationsdes/design/gdc02_jaime_griesemer.pdf© 2011 SQUARE ENIX CO., LTD. All rights

Oct.8, 2011

reserved36

World Representation (one of KR)
World Representation （WR）
= KR for Game Stage（Representation based on Waypoint or Navigation Mesh）◆ FPS◆ Guerrilla◆ SCEE/SEGA◆ PS2◆2004/2005（例） Waypoints with 8-direction LOS(visible distance) (Killzone)
Straatman, R., Beij, A., Sterren, W.V.D., "Killzone's AI : Dynamic Procedural Combat Tactics", 2005
http://www.cgf-ai.com/docs/straatman_remco_killzone_ai.pdf

Variation of World Representation
Distribution Map

Damian Isla,"Building a Better Battle: HALO 3 AI Objectives",
http://www.bungie.net/inside/publications.aspx

Waypoints with LOS

Territory Representation

Killzone

Halo2

Tactical Point System

Tactical Map Clustering

NavMesh-Waypoint
Hierarchical Representation

Halo

Killzone2

Left 4 Dead

Michael Booth, "The AI Systems of Left 4 Dead," Artificial Intelligence and Interactive Digital Entertainment
Oct.8, 2011
Conference , http://www.valvesoftware.com/publications.html

Assassin’s Creed
Alex J. Champandard, Remco Straatman, Tim Verweij, "On the AI Strategy for KILLZONE 2's Bots”
38
http://aigamedev.com/open/coverage/killzone2/

Agent Architecture
AI

Recognitio

Decision
MakingMotionMakingMemorySensorEffecter

Knowledge Representation
World RepresentationGame World
Represent itself
Game World

Agent Architecture
AI

Recognitio

Decision
MakingMotionMakingMemorySensorEffecterKR
WR
Game WorldKR and WR enforce and expand sensors.

Agent Architecture
AI

Recognition

KR
SensorWR

Decision
MakingMotionMakingMemoryEffecterKR
WR
Game World
Type of KR and WR = Type of Knowledge in Memory (via sensors)

… And one more conceptAffordance Representation
Affordance Representation= Actions enable in the environment

The car is afford to move to one direction.
= movable to one direction for AI.






Genre：SciFi-FPS
Developer： BUNGIE Studio
Publisher : Microsoft
Hardware: Xbox, Windows, Mac
Year：
Year 2004[Affordance Representation] for the car- movable- direction (10, 120, 40)

Affordance Representation
Affordance Representation= Actions enable in the environment

Attackable

Eatable

Genre：Action
Developer： FROM SOFTWARE
Publisher : CAPCOM
Hardware: PSP
Year：
Year 2011

Each object has Affordance Representation.
[CEDEC2011]
Namiki Kosuke,"Afforfance-oriented AI for PokaPoka Airu Village"
http://cedil.cesa.or.jp/session/detail/697

Affordance Representation
Affordance Representation= Actions enable in the environment







Genre：Action
Developer： FROM SOFTWARE
Publisher : CAPCOM
Hardware: PSP
Year：
Year 2011

http://www.4gamer.net/games/100/G010022/20110906085/

Each object has Affordance Representation.
= Each object suggests “Enabled-Action” to AI.
[CEDEC2011]
Namiki Kosuke,"Afforfance-oriented AI for PokaPoka Airu Village"
http://cedil.cesa.or.jp/session/detail/697

Agent Architecture
AI

Recognitio

KR
SensorWR

Decision
MakingMemoryEnable-Action-List

MotionMakingEffecter

Knowledge Representation
World Representation
Affordance RepresentationGame World
Affordance Representation = Afforded Action-List in the Environment (via sensor)

Agent Architecture
AI

Recognition

KR
SensorWR

Decision
MakingMemoryEnable-Action-List

Attack-able to Enemy A
Eat-able to Object B
Movable to Car C
MotionWalk-able on Bridge D
MakingEat-able to Object E

Effecter

Knowledge Representation
World Representation
Affordance RepresentationGame World
Affordance Representation = Afforded Action-List in the Environment (via sensor)

(4) Memory Structure & Management
Memory has two hierarchical structure(a) time-hierarchical structure(b) logic-hierarchical structure

Information

Memory(4) Memory Structure & Management
Memory has two hierarchical structure(a) time-hierarchical structure(b) logic-hierarchical structure

Information

Memory(4) Memory Structure & Management
Memory has two hierarchical structure(a) time-hierarchical structure(b) logic-hierarchical structure

Working Memory

MemoryShort-term Memory
Long-term Memory

Fixed (Static)
MemoryInformation

Information propagate through hierarchical-Memory-Structure.

Working Memory

MemoryShort-term Memory
Long-term Memory

Fixed (Static)
MemoryInformation

Information propagate through hierarchical-Memory-Structure.

Working Memory

MemoryShort-term Memory
Long-term Memory

Fixed (Static)
MemoryInformation

Information propagate through hierarchical-Memory-Structure.

Working Memory

MemoryShort-term Memory
Long-term Memory

Fixed (Static)
MemoryInformation

Information propagate through hierarchical-Memory-Structure.

Working Memory

MemoryShort-term Memory
Long-term Memory

Fixed (Static)
MemoryMultiple-Time-Scale-hierarchical-Memory-Structure.

Information

1 Frame Update
Working Memory
10 Frame Update
MemoryShort-term Memory

60 Frame UpdateLong-term Memory

No Update
Fixed (Static)
MemoryInformation

1 Frame Update
Working Memory
10 Frame Update
MemoryShort-term Memory

60 Frame UpdateLong-term Memory

No Update
Fixed (Static)
MemoryAbstraction

Memory has two hierarchical structure(a) time-hierarchical structure(b) logic-hierarchical structure

(5) Decision Making
AI

Recognition

KR
SensorWR

Decision
MakingMemoryEnable-Action-List

Knowledge Representation
World Representation
Affordance RepresentationGame World

MotionMakingEffecter(5) Decision Making
Decision Making Techniques are classified to 6 types

Rule-based AI
State-based AI

Decision
MakingBehavior-based AI
Goal-based AI
Task-based AI
Utility-based AI“Something- Based” means a Decision-Making-Method use
Something as unified-form of thinking.

(5) Decision Making
Decision Making Techniques are classified to 6 types
The Form of thinking
Rule-based AI
State-based AI

Decision
MakingBehavior-based AI
Goal-based AI
Task-based AI
Utility-based AI“Something- Based” means a Decision-Making-Method use
Something as unified-form of thinking.

(5) Decision Making
Rule-based AI







Genre：Simulation
Developer： Maxis
Publisher : EA
Hardware: PC, PS3
Year：
Year 2009[GDC2010] Richard Evans, "Modeling Individual Personalities in The Sims 3"
http://www.gdcvault.com

(5) Decision Making
State-based AI







Genre：SciFi-FPS
Developer： id Software
Publisher : GT Interactive
Hardware: PC
Year：
Year 1996
http://www.idsoftware.com/

A Practical Analysis of FSM within the domain of first-person shooter (FPS) computer game
http://ai-depot.com/FiniteStateMachines/FSM-Practical.html

(5) Decision Making
Task-based AI

HTN (Hierarchical Task Network)






Genre： FPS
Developer： Guerrilla Games
Publisher : SCE
Hardware: PlayStation 3
Year 2009Year：

Based on: Alex Champandard, Tim Verweij, Remco Straatman, "Killzone 2 Multiplayer Bots",
http://files.aigamedev.com/coverage/GAIC09_Killzone2Bots_StraatmanChampandard.pdf

(5) Decision Making
Behavior-based AI







Genre：SciFi-FPS
Developer： BUNGIE Studio
Publisher : Microsoft
Hardware: Xbox, Windows, Mac
Year：
Year 2004

Damian Isla (2005), Handling Complexity in the Halo 2 AI,
GDC Proceedings.,
http://www.gamasutra.com/gdc2005/features/20050311/isla_01.shtml

Behavior-Tree (has become very popular method .)(1) Hierarchical Structure of Box(2) Each box has some behaviors(3) Each box has one selection-rule(random, sequential, priority-order…)(4) Finally, one behavior is selected at end-of-tree.

(5) Decision Making
Utility-based AI

The Sims’ Motive Engine







Genre：Simulation
Developer： Maxis
Publisher : EA
Hardware: PC
Year：
Year 2000

Ken Forbus, “Simulation and Modeling: Under the hood of The Sims” (NorthWerstern University)
http://www.cs.northwestern.edu/%7Eforbus/c95-gd/lectures/The_Sims_Under_the_Hood_files/frame.htm

(5) Decision Making
Goal-based AI
Goal-Oriented Action Planning (GOAP)No Condition

PlannerPick up weapon Chaining = Matching “Preconditon” and “Result”
Has weapon

Has weapon

Jeff Orkins, "Goal-Orientd Action Planning"
http://web.media.mit.edu/~jorkin/goap.html

Load Weapon
Chaining
WeaponLoadedWeaponLoadedAttackChaining

Precondition

ActionResultTarget A
Dead

TargetDeadGoal

(5) Decision Making
Goal-based AI
Hierarchical Goal Oriented Planning
Goal

Goal

Goal







Goal

Genre：Robot Action
Developer： FROM SOFTWARE
Publisher : SEGA
Hardware: XBox360
Year：
Year 2006

CEDEC2006「クロムハウンズにおける人工知能開発から見るゲームAIの展望」（三宅陽一郎）
http://cedil.cesa.or.jp/session/detail/50

Goal

Goal

Goal

Goal

Goal

Goal

Goal

Goal

(6) Motion Making
AI

Recognition

KR
SensorWR

Decision
MakingMemoryEnable-Action-List

Knowledge Representation
World Representation
Affordance RepresentationGame World

MotionMakingEffecter(6) Motion Making

Decision
MakingMotionMakingIn this field, there are many, many models between DM and Motion Making.

(6) Motion Making
Rule-based AI
State-based AI

Decision
MakingBehavior-based AI
Goal-based AI
Task-based AI
Utility-based AI

discrete

MotionMakingGap

continuous(6) Motion Making
Rule-based AI
State-based AI

Decision
MakingBehavior-based AI
Goal-based AI
Task-based AI

Research
Theme

Utility-based AI

discrete

MotionMakingGap

continuous(6) Motion Making
AI

Recognition

KR
SensorWR

Decision
MakingMemoryEnable-Action-List

Knowledge Representation
World Representation
Affordance RepresentationGame World

MotionMakingBody &
Animation
Representation

EffecterResearch Themes(1)Architecture(2)Knowledge/World/Affordance Representation(3)Memory Structure & Memory management(4)Sensor(5)Decision Making…and Synthesis of all these things to make“Real” intelligence.

CHARACTER NAVIGATION

Character Navigation
Moving Character in the Environment







Genre：FPS
Developer： TURTLEROCK STUDIO
Publisher : Valve Software
Hardware: PC
Year：
Year 2000

The Official Counter-Strike Bot by Michael Booth (GDC2004)
http://aigamedev.com/insider/presentation/official-counter-strike-bot/Navigation Problem
Game Stage becomes bigger and complex.
2000

2005

2010
Year
Number of meshes

1000-

10000-

40000-

Number of meshes has been increasing.
Problems:(1) How to make large scale navigation meshes.
(2) How to maintenance large scale meshes.
(3) How to debug large scale meshes.

Navigation Mesh Auto-generation







Genre：Robot Action
Developer： FROM SOFTWARE
Publisher : SEGA
Hardware: XBox360
Year 2006
Year：

CEDEC2006「クロムハウンズにおける人工知能開発から見るゲームAIの展望」（三宅陽一郎）
http://cedil.cesa.or.jp/session/detail/50

40000-70000 meshes
Auto-generation from collision models
But mesh quality is not good.

AI in Game World
Game Mechanism

Meta AI

Game World
Techniques(= Environment = Game Stage =Procedural
Level Design)(Auto-generation, Auto-Control)

AI Character(=NPC)
Character AI(Brain)META-AI

Meta-AI
Autonomous Game Mechanism(Game Mechanism AI)
Ever, Game Mechanism is fixed at release.
It makes game content volume limited.

But Game has become bigger and complex.

Make game mechanism intelligent !
Meta AI = Intelligent Game Mechanism- Recognize Game Status in real-time- Control (Act on, Influence)Game Status dynamically

http://www.valvesoftware.com/publications.html

AI in Game World
Meta AI
Sensor &Game
Mechanism
actionRecognition

Game World(= Environment = Game Stage = Level Design)
Sensor &Recognition

actionAI Character(=NPC)

Left 4 Dead
AI Director controls NPC spawning distribution and game-play-pacing.







Genre：Online Action
Developer： VALVE SOFTWARE
Publisher : VALVE SOFTWARE
Hardware: PC
Year 2008
Year：

Using nav-mesh for recognizing and controlling
Real-time status of game.

Michael Booth, "Replayable Cooperative Game Design: Left 4 Dead," Game Developer's Conference, March 2009 http://www.valvesoftware.com/publications.html

Left 4 Dead – AI Director
Meta AI recognize game status in real-time

Predicting player’s route and spawning monsters dynamically.

Michael Booth, "Replayable Cooperative Game Design: Left 4 Dead," Game Developer's Conference, March 2009 http://www.valvesoftware.com/publications.html

AI Director decide when enemies are spawned.
DESIREDPOPULATION

USER’S INTENSITYACTUAL POPULATIONAI Director makes users relax, and break relax repeatedly.

Build Up …プレイヤーの緊張度が目標値を超えるまで敵を出現させ続ける。
Sustain Peak … 緊張度のピークを3-5秒維持するために、敵の数を維持する。
Peak Fade … 敵の数を最小限へ減少して行く。
Relax … プレイヤーたちが安全な領域へ行くまで、30-45秒間、敵の出現を最小限に維持する。

Michael Booth, "Replayable Cooperative Game Design: Left 4 Dead," Game Developer's Conference, March 2009 http://www.valvesoftware.com/publications.html

Procedural

PROCEDURAL TECHNIQUESAI in Game World
Meta AI

Game Mechanism

Game World(= Environment= GameStage = Level Design)
Procedural
Techniques(Auto-generation, Auto-Control)
AI Character(=NPC) AI
Character(Brain)Procedural Techniques
Auto-generation, Auto-Control
Recent game has many, many asset data such as
Terrain, Characters, Weather, Object, Trees, lines….

- It’s too hard work and needs big budget.
- Fixed data makes fixed Game Content.

Dynamically generate contents in game in real-time

Procedural Techniques- make terrain, buildings, and vegetation dynamically.
- make scenario and lines in game in real-time.

DUNIA ENGINE : FarCry2 Procedural Engine







Genre：FPS
Developer： Ubisoft
Publisher : Ubisoft
Hardware: PC
Year：
Year 2008

Procedural techniques (for 50kmx50km island)- Vegetation and its animation auto-generation- Fire-propagation- Weather

http://www.farcry2-hq.com/downloads,18,dunia-engine-nr1.htm

SYNTHESISClassic Game Structure (1970-)
Game Mechanism

Game World (fixed)(= Environment = Game Stage = Level Design)

AI Character(=NPC)

AI is a part of level design, and game system (mechanism) controls AI characters.

Classic Game Structure (1970-)
Game Mechanism

Game World(= Environment = Game Stage = Level Design)

AI Character(=NPC)

AI is a part of level design, and game system (mechanism) controls AI characters.

Game Structure (1995-)
Game Mechanism

Game World(= Environment = Game Stage = Level Design)
Sensor &Recognition

actionAI Character(=NPC)
Autonomous AI

AI Character becomes autonomous. AI by itself sense and take actions.

Game Structure (2000-)
Game Mechanism
Game World(= Environment= GameStage = Level Design)
Procedural
Techniques(Auto-generation, Auto-Control)
Sensor &Recognition

actionAI Character(=NPC)
Autonomous AI

Game World becomes more dynamical by procedural techniques.

Game Structure (2008-)
Game Mechanism
Meta AI
Sensor &Recognition

actionGame World(= Environment= GameStage = Level Design)
Procedural
Techniques(Auto-generation, Auto-Control)
Sensor &Recognition

actionAI Character(=NPC)
Autonomous AI

Meta AI makes game mechanism itself more dynamical.

… AND THE FUTURE ?

Game Structure (2012-)
Game Mechanism
Meta AI

Game World
Procedural Techniques(Auto-generation, Auto-Control)

AI Character(=NPC)
Autonomous AI

Three AI Component will connect each other and makes new game.

Imagine• Imagine “Meta AI uses Procedural Techniques”• Imagine “Meta AI uses autonomous AI”• Imagine “Procedural AI generation”• …. To be continued

THANK YOU SO MUCH!