2013 fighting game artificial intelligence competition

Fighting Game Artificial Intelligence Competition

Platform

Feiyu Lu, Kaito Yamamoto, Luis H. Nomura, Syunsuke Mizuno, YoungMin Lee,

and Ruck Thawonmas

Intelligent Computer Entertainment Laboratory,Ritsumeikan University

2013 IEEE 2nd Global Conference on Consumer Electronics (GCCE 2013), October 3, 2013

Video Games and Fighting Games Artificial Intelligence Game AI Competitions in 2013 Architecture and Game System Contest Rules and Result Conclusions and Future Work

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Electronic game

Human interaction with a user interface

Generate visual feedback on video device

Video Games and Fighting Games


Tekken Namco 41.4 million (as of 2011)

Street Fighter Capcom 34 million (as of 2012)

Mortal Kombat Midway/Warner Bros.

26 million (as of 2007)

Super Smash Bros. Nintendo 23.6 million (as of 2013)

Soul Calibur Namco 13.4 million (as of 2012)

Dead or Alive Tecmo 7.95 million (as of 2008)

Video Games and Fighting Games


Video Games and Fighting Games Artificial Intelligence Game AI Competitions now Architecture and Game System Contest Rules Conclusions and Future Work



Artificial + Computational Intelligence

Finite state machines / fuzzy state machines / neural networks

Represents NPC (non-player character)

Run competition to compare and find high performance AIs

Artificial Intelligence


Video Games and Fighting Games Artificial Intelligence Game AI Competitions in this year Architecture and Game System Contest Rules Conclusions and Future Work



Game AI Competitions

AIIDE StarCrafthttp://webdocs.cs.ualberta.ca/~cdavid/starcraftaicomp/



CIG 2013http://ls11-www.cs.uni-dortmund.de/rts-competition/start



Angry Birdshttp://aibirds.org/



Physical Travelling Salesmanhttp://www.ptsp-game.net/



Platformerhttp://platformersai.com/


Video Games and Fighting Games Artificial Intelligence Game AI Competitions now Architecture and Game System Contest Rules Conclusions and Future Work



Architecture and Game System (1/2)

Platform’s architecture

This illustration shows the interactions between AIs or humans

AI and human player can get information per frame (the smallest time unit of the game, 1 frame = 16.66 msec) from game, and send their commands to game to control their characters2013 IEEE 2nd Global Conference on Consumer Electronics (GCCE 2013), October 3, 2013

Architecture and Game System


Actions have to be chosen and input for each frame, or the character will not do anything

Information sent to AIs will have a simulated delay – to prevent AI players using an unfair reaction speed

Architecture and Game System (2/2)


Skill system

Players use some skills and moving actions to fight

In the game, a skill usually has 3 stages – Startup, Active and Recovery

Skill System (1/5)


Skill System (2/5)


Skill System (3/5)

Startup 1st stage

Prepare to attack No attack box so no

damage


Skill System (4/5)

Active 2nd stage

The small red box -- attack box -- can be seen on the character’s arm

In these frames, if the opponent’s attack hit box coincide with this attack box, the opponent will be damaged


Skill System (5/5)

Recover 3rd stage Recover to normal

status

Special frame: cancelable

Some skills can be used during cancelable frames





Only one character “KFM-prototype” can be used. One game has 3 rounds. Each round has a 5-

second ready time and 60-second fighting time. The characters' positions will be reset when time

over, and the system starts a new round if it is not the last round.

The game score will be calculated as

And higher one is the game’s winner.

Contest Rules


BitterCoffeeFTGAI Nanjing ZhiFeng Multimedia Co., Ltd., China BloodMoon Nanjing XinYiWei Software Co., Ltd., China Buakaw Bangkok University, Thailand Death Rose FTGAI ? Hybrid Bangkok University, Thailand Kaiju Bangkok University, Thailand Kong Fu King Donghu college, Wuhan University, China SejongAI Sejong University, Republic of Korea T TAIST-Tokyo Tech, Thailand Tony Jaa Bangkok University, Thailand

Team List (Alphabetical order)


BitterCoffeeFTGAI

Fighting Game AI Competition

Qi Jin BachelorSoftware Engineer of Nanjing ZhiFeng Multimedia Co., Ltd.

E-mail : [email protected]


BitterCoffeeFTGAI

Intro of AI ：

AI that uses a

“Random move action + Rule base attack skill”

Way to fight.


BitterCoffeeFTGAI

Way of thinking ：Detective the distance to opponent ， random select some skill

(prevent a rule-base defense) to attack according to the distance. Some as:

e.g:distance less than 100 and on the ground will cast THROW_A or THROW_B;

e.g:distance greater than 100 and on the ground will cast STAND_D_DF_FA,STAND_D_DF_FB or STAND_D_DF_FC(when energy > 300)

and so on.


BloodMoon AI

FTGAIC

2013.9.262013 IEEE 2nd Global Conference on Consumer Electronics (GCCE 2013), October 3, 2013

AI’s Outline

1、 A rule base AI

2、 Get information like distance, high and character’s status, and then select a fitness skill in case to attack.

Cheung Yi Chun Nanjing XinYiWei Software Co., Ltd.

E-mail : [email protected] IEEE 2nd Global Conference on Consumer Electronics (GCCE 2013), October 3, 2013

Buakaw: Thai Fight

Wisarat PhuranantanondAngkana SuwanjatupornKingkarn Sookhanaphibarn

School of Science and Technology

BANGKOK UNIVERSITY2013 IEEE 2nd Global Conference on Consumer Electronics (GCCE 2013), October 3, 2013

BuakawMain concept is based on game

experience heuristics.We analyzed our bot position

compared to location on screen and distance between players.

If our position is in the middle of screen that mean the distance between players is always in range for the fireball action.


BuakawWe divided the distance between

players into three categories.◦Far◦Mid◦Near

Within each category a rule-based action is used. For example:◦Far: use mainly a fire ball action◦Mid: check the opponent’s action to

determine the response.◦Near: use a counter attack strategy based on

opponent’s action. 2013 IEEE 2nd Global Conference on Consumer Electronics (GCCE 2013), October 3, 2013

Death Rose FTGAI

Lu liang 　 / [email protected]


Rule base Defense AI

A good defender is better than a fury attacker !

So when there is no better tactic, try to defense more and wait counter chance.

According to the distance, guard the fireball and wait opponent move or escape / counter-attack.


Thanarat JaruenyingAngkana Suwanjatuporn

Worawat Choensawat

Hybrid

School of Science and TechnologyBANGKOK UNIVERSITY


HybridWe presents a rule-based strategy based

on fighting states.Two states are determined which are

Wining and Losing.Wining state: our HP > opponent’s HPLosing state: our HP < opponent’s HP

For each state, we can divided into two cases as follows:Far: distance of players over a threshold. Near: distance of players less then the

threshold. 2013 IEEE 2nd Global Conference on Consumer Electronics (GCCE 2013), October 3, 2013

HybridAfter we determined the state and the

case, we used rule-based method to define the action.

The rule based method is based on four parameters as follows:Enemy’s ActionEnemy’s status: Air, Stand, Crouch or downOur energy: to determine which attack action

to be used.Distance between players

We also add a cornering prevention to avoid our character get trap in the corner of screen.


KAIJUParanee Apiromsanee

Angkana Suwanjatuporn

Kingkarn Sookhanaphibarn

School of Science and Technology

BANGKOK UNIVERSITY


KAIJU We used an adaptive decision to determine a

character action based on the opponent’s attacks.

The adaptive decision can be divided into two states as follows: Counter attack Defense

The reason for dividing the decision into two states is below: There is a large amount of opponent actions. Based

on our experiments, counter attack actions can be used only for some actions . Therefore, we used a defense strategy for actions that counter attack actions cannot be used. 2013 IEEE 2nd Global Conference on

Consumer Electronics (GCCE 2013), October 3, 2013

KAIJU The decision is based on three main

parameters:Distance between playersEnemy skillOur HP

Simple is the best!


KONG FU KING

2013 IEEE 2nd Global Conference on Consumer Electronics (GCCE 2013), October 3,

2013

Intro

A simple AI that using rule base algorism.

When fighting in long range, copy enemy’s action.

When fighting in a close range, use a throw.

When fighting in a middle range, use fireball.

Lu Xiaoming

Donghu college Wuhan University

E-mail : xiswspxr@hotmail.

com

2013 IEEE 2nd Global Conference on Consumer Electronics (GCCE 2013), October 3,

2013

Fighting Game AI

Sejong University


Introduction

• AI Name : SejongAI

• Advisor – Kyung Joong Kim

• Developers – Dong Hyun Jang– Kyoung Jun Ahn

• Affiliation– Sejong University, South Korea


Outline

1. Using Skills

2. Strategies


Outline - Using Skills

• STAND_D_DF_FA• STAND_D_DF_FC• STAND_D_DB_BB• THROW_HIT• AIR_UB


Outline - Strategies

• AI’s first attack skill is “STAND_D_DB_BB”.

• And the major attack skill is “STAND_D_DB_BB”.

• When “STAND_D_DB_BB” hits opponent and knock down, we will use “AIR_UB” or “STAND_D_DF_FA” or “STAND_D_DF_FC”.

• Our Agent’s major strategy is knock down.2013 IEEE 2nd Global Conference

on Consumer Electronics (GCCE 2013), October 3, 2013

T

Fighting Game AI Competition

Mr.Phakhawat Sarakit (Toon)Master Degree Student

TAIST Tokyo-TechInformation and Communication Technology for Embedded Systems : ICTES

E-mail : [email protected]


AI’s OutlineMeasure-Sense-Action cycle .Measure distance X between opponent and my AI see enemy action and thing

about it then find the best way to fight back the enemy.Fininte-State Machine(FSM).

I don’t know anymore. I think it’s a simple and the best I had ever have


TONY JAAAyuvat TrongkronboonyavatAngkana SuwanjatupornWorawat Choensawat

School of Science and TechnologyBANGKOK UNIVERSITY


Methodology

We implemented a rule-based model by using a state of our character.

Character state can be divided into three states as follows: Fully Attack: the character losing HP at

minimal range. Attack & Defense: the character keeps losing

HP. Fully Defense: the character losing HP over a

maximum threshold.


Methodology

For each state, a rule-based method is used within the state.

For the rule-based method, four main parameters are considered. Distance between players Enemy’s action Energy to determine which skill to be used Enemy’s status


BitterCoffee

FTGAI BloodMooN BuaKaw DeathRose Hybrid KaijuKongFuKin

g SejongAI T TonyJaa

TotalScore

s Rank

BitterCoffee FTGAI

　

　

434

1347

560

1348

484

1302

443

1194

145

356

500

1384

310

759

120

358

337

811 8859 8

　 448 341 434 353 105 500 240 124 88

　 465 447 384 398 106 384 209 114 386

BloodMooN

565

1650

　

　

417

1247

386

1203

361

1093

0

21

720

2010

309

872

25

260

100

160 8516 9

551 　 413 500 343 0 705 295 121 52

534 　 417 317 389 21 585 268 114 8

BuaKaw

440

1650

582

1750

　

　

66

801

802

1878

688

1976

500

1533

238

1387

168

1186

561

17551391

6 5

658 586 　 735 566 576 500 499 634 739

552 582 　 0 510 712 533 650 384 455

DeathRose

515

1695

613

1795

933

2197

　

　

272

1103

561

1757

666

1957

243

777

21

324

261

10971270

2 7

565 500 264 　 400 505 666 282 90 535

615 682 1000 　 431 691 625 252 213 301

Hybrid

556

1803

638

1904

197

1119

727

1895

　

　

201

1219

694

2032

326

1080

186

734

360

11751296

1 6

646 656 433 600 　 336 591 267 231 355

601 610 489 568 　 682 747 487 317 460

Kaiju

854

2641

1000

2978

311

1021

438

1240

798

1778

　

　

1000

3000

484

1430

309

686

587

18581663

2 3

894 1000 423 494 663 　 1000 668 124 750

893 978 287 308 317 　 1000 278 253 521

KongFu King

500

1614

279

987

500

1466

333

1041

305

965

0

0

　

　

182

645

89

559

187

904 8181 10

499 294 500 333 408 0 　 122 212 401

615 414 466 375 252 0 　 341 258 316

SejongAI

689

2238

690

2125

761

1610

756

2220

673

1917

515

1567

817

2352

　

　

670

1473

190

11681667

0 2

759 704 500 717 732 331 877 　 268 534

790 731 349 747 512 721 658 　 535 444

T

879

2639

975

2738

835

1815

978

2673

813

2263

690

2311

910

2438

329

1524

　

　

666

19822038

3 1

875 878 365 909 768 875 787 731 　 653

885 885 615 786 682 746 741 464 　 663

TonyJaa

662

2186

899

2837

438

1242

738

1900

639

1822

412

1140

812

2393

809

1829

333

1015

　

　1636

4 4

911 947 260 464 644 250 598 465 346 　613 991 544 698 539 478 983 555 336 　

Final Ranking

Team name Total scores Ranking

T 20383 1

SejongAI 16670 2

Kaiju 16632 3

TonyJaa 16364 4

BuaKaw 13916 5

Hybrid 12961 6

DeathRose 12702 7

BitterCoffeeFTGAI 8859 8

BloodMooN 8516 9

KongFuKing 8181 102013 IEEE 2nd Global Conference on Consumer Electronics (GCCE 2013), October 3, 2013

1st Round http://youtu.be/wLWxg6IOq7g

2nd Round http://youtu.be/QgKwqfERo4w

3rd Round http://youtu.be/gamOUgUTpA8


Video Clips of the Game Betweenthe Runner-Up SejongAI (P1) and

the Winner T (P2)

http://youtu.be/wLWxg6IOq7g_



http://youtu.be/QgKwqfERo4w

http://youtu.be/gamOUgUTpA8

Video Games and Fighting Games Artificial Intelligence Game AI Competitions in 2013 Architecture and Game System Contest Rules Conclusions and Future Work



We have implemented our fighting game AI platform and reported the first competition.

In the future, with the support from Dimps, we plan to design more sample characters and run a sequence of competitions at related international conferences.

You are welcome to participate in these competitions. http://www.ice.ci.ritsumei.ac.jp/~ftgaic/

Conclusions and Future Work
