2016 IEEE CIG StarCraft AI Competition
( https://sites.google.com/site/starcraftaic/ )
Cheong-mok Bae, Seonghoon Yoon, Seok Min Hong
Kyung-Joong Kim
Cognition and Intelligence Lab (http://cilab.sejong.ac.kr)
Sejong University, Seoul
Republic of Korea
StarCraft Brood War
• Real-time strategy game
• Released in 1998 by
Blizzard
• Three races
• Protoss, Terran, Zerg
• Play time
• Several minutes ~ Hours
• Goal of the game
• Eliminate all the buildings
of opponents
Resource
Management
Uncertainty
Handling
Micro
Management
Decision
Making
Real-Time
Response
StarCraft AI Competition
• Annual event since 2010
• Three independent
competitions (IEEE CIG, AIIDE,
and SSCAIT)
• C++ or JAVA programming
using BWAPI (Brood War API)
• AI vs. AI matches
• Fully automated tournament
software
• 8 days running with 17
machines
Basic Rules
AI1
AI2
AI4 AI5
AI3
• Full round-robin style tournament
• 100 Rounds with 5 maps
• File I/O is allowed
• Used for long-term adaptation
• 42 milliseconds response time
requirement
• 1 hour time limit for each match
2016 Update on Rules
• Open source policy
• All participants’ source code will be available after this competition
• Introducing qualifying and final tournaments
• Qualifying
• Select top players (50%) to advance 2nd stage
• Final
• Full round-robin tournaments of the top players
• Winner is determined from the 2nd Stage Qualification
(All entries)
Final
(Half)
Number of Games Played
70
2340
8279
5579
10251
20788
40
4050
2500
4680
2730
14800
0
5000
10000
15000
20000
25000
2010 2011 2012 2013 2014 2015 2016
AIIDE
CIG
[Source] 2010~2015 data from https://webdocs.cs.ualberta.ca/~cdavid/starcraftaicomp/report2015.shtml
Entrants
• 16 participants from 13 countries
• 9 Updated or newcomer submissions
• 7 Last year’s bot without change (Re-entrance)
AIUR Bonjwa OpprimoBot Overkill Salsa TerranUAB UAlbertaBot
Last
Year’s bot
(Re-entrance)
LetaBot MegaBot SRbotOne XelnagaII ZiaBot Iron tscmoo Tyr ZZZKBot
Newcomers
& Updated
Entrants (Details)
Aiur
Bonjwa
OpprimoBot
Overkill
Salsa
TerranUAB
UAIbertaBot
LetaBot
MegaBot
SRbotOne
XelnagaII
ZiaBot (Navinad)
Iron
tscmoo
Tyr
ZZZKBot
Protoss Florian Richoux
Dustin Dannenhauer
Johan Hagelback
Sijia Xu
Pablo Garcia Sanchez
Filip Bober
David Churchill
Martin Rooijackers
Anderson Rocha Tavares
Johan Kayser
Cheong-mok Bae
Sungguk Cha
Igor Dimitrijevic
Vegard Mella
Simon Prins
Chris Coxe
Terran
Terran
Zerg
Zerg
Terran
Random
Terran
Protoss
Terran
Protoss
Zerg
Terran
Terran
Terran
Zerg
Université de Nantes
Lehigh University
Linnaeus University
-
University of Granada
Poznan Univ. of Technology
University of Alberta
Maastricht University
Universidade Federal de Minas
UQAM
Sejong University
UNIST
-
-
Utrecht University
-
-
-
-
-
-
-
-
Student
Student
Student
Student
-
-
-
Programmer
SW Engineer/Developer
Race Distribution
1
2
3
4
5
6
7
8
9
0
2013 2014 2015 2016
Zerg
Terran
Protoss
Random
Results
Announcement
Result – Qualifying Stage
Bot
Iron
Tscmoo
LetaBot
Overkill
MegaBot
UAlbertaBot
ZZZKBot
Aiur
Tyr
Ziabot
TerranUAB
SRbotOne
OpprimoBot
XelnagaII
Bonjwa
Salsa
Race Games
1500
1498
1500
1499
1499
1499
1499
1498
1499
1497
1498
1499
1498
1497
1499
1497
Terran
Terran
Terran
Zerg
Protoss
Random
Zerg
Protoss
Terran
Zerg
Terran
Terran
Terran
Protoss
Terran
Zerg
Win
1188
1153
1111
1064
1051
1038
1037
946
924
695
502
332
331
310
284
22
Loss
312
345
389
435
448
461
462
552
575
802
996
1167
1167
1187
1215
1475
Win%
79.2
76.97
74.07
70.98
70.11
69.25
69.18
63.15
61.64
46.43
33.51
22.15
22.1
20.71
18.95
1.47
AvgTime
14:11
14:15
13:34
11:37
11:44
9:59
7:23
13:20
17:19
9:56
14:11
14:45
16:46
13:34
12:05
10:53
Hour
30
8
38
16
18
30
0
32
77
21
18
19
0
51
32
0
Crash
22
27
15
22
102
0
0
7
25
183
72
3
204
677
1
480
Timeout
7
0
0
0
4
0
0
0
0
114
1
6
0
226
0
119
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
- - 11988 11988 11988 - 12:51 195 1840 477Total
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
WinRate
Round Number
Qualification: Win Ratio Over Time
Iron
tscmoo
LetaBot
Overkill
MegaBot
UAlbertaBot
ZZZKBot
Aiur
Tyr
Ziabot
TerranUAB
SRbotOne
OpprimoBot
XelnagaII
Bonjwa
Salsa
Result – Final Stage
Bot
Tscmoo
Iron
LetaBot
ZZZKBot
Overkill
UAlbertaBot
MegaBot
Aiur
Race Games
700
700
700
699
700
699
700
700
Terran
Terran
Zerg
Random
Protoss
Win
456
381
376
371
360
343
266
246
Loss
244
319
324
328
340
356
434
454
Win%
65.14
54.43
53.71
53.08
51.43
49.07
38.00
35.14
AvgTime
15:29
15:23
13:45
8:42
13:16
11:22
10:56
12:54
Hour
3
17
8
1
15
22
5
15
Crash
0
14
0
0
4
0
100
2
Timeout
0
3
0
0
0
1
6
0
Rank
1
2
3
4
5
6
7
8
- - 2799 2799 2799 - 12:43 43 120 10Total
Terran
Zerg
Protoss
Congratulation!
Winner of 2016 IEEE CIG StarCraft AI Competition
TSCMOO by Vegard Mella from Norway
Rank Change
Bot
Iron
Tscmoo
LetaBot
Overkill
MegaBot
UAlbertaBot
ZZZKBot
Aiur
Rank
1
2
3
4
5
6
7
8
Win%
79.2
76.97
74.07
70.98
70.11
69.25
69.18
63.15
Qualification
Bot
Tscmoo
Iron
LetaBot
ZZZKBot
Overkill
UAlbertaBot
MegaBot
Aiur
Rank
1
2
3
4
5
6
7
8
Win%
65.14
54.43
53.71
53.08
51.43
49.07
38.00
35.14
Final
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
WinRate
Round Number
Result - Stage2: Win Percentage Over Time
tscmoo
Iron
LetaBot
ZZZKBot
Overkill
UAlbertaBot
MegaBot
Aiur
Winner
Tscmoo
• Comeback with Terran Bot (Last year: Zerg)
• It’s good with vultures
• Use neural network ‘Long Short-Term Memory (LSTM)’ for
some high level decisions (which units to build) to provide
hints to bunch of heuristics
• Remember what happen in previous games, and do
something reasonable in response next game
Terran
2nd Rank
Iron
• A successor of “Stone”(Rank 19/22 in AIIDE 2015)
• Multi-Agent System, each controlled unit is an Agent.
(Agent behave to avoid blocking situations, indecision,
predictability.)
• Iron’s unis have simple behaviors like “harass his main” or
“keep alive”
Terran
3rd Rank
LetaBot
• Use A* and DFS algorithm to find a build place for block
choke point (set up barricade)
• Use pathfinding algorithm for efficient resource gathering
• Use Influence map to calculate units’ attack power
• Resource gathering algorithm based on linear algebra
Terran
7th Rank
MegaBot
• Proof-of-Concept bot that plays the strategy selection
Reference: To appear in AIIDE 2016
Tavares, Azpurua, dos Santos, Chaimowicz.“Rock, Paper, StarCraft:
Strategy Selection in Real-time Strategy Games.”
• Use codes of Skynet, Xelnaga, and NUSBot
• Select strategy at the start phase through modified epsilon-greedy
𝑉 𝑠, 𝑜 ← 1 − 𝛼 ∗ 𝑉 𝑠, 𝑜 + 𝛼 ∗ 𝑟𝑒𝑠𝑢𝑙𝑡
protoss
Highlight
Acknowledgements
David Churchill
(University of Alberta)
Organizer of AIIDE StarCraft AI
Competition
Michal Certicky and his team members
(Czech Technical University in Prague)
Organizer of Student StarCraft AI Tournament
QnA

Starcraft 2016

  • 1.
    2016 IEEE CIGStarCraft AI Competition ( https://sites.google.com/site/starcraftaic/ ) Cheong-mok Bae, Seonghoon Yoon, Seok Min Hong Kyung-Joong Kim Cognition and Intelligence Lab (http://cilab.sejong.ac.kr) Sejong University, Seoul Republic of Korea
  • 2.
    StarCraft Brood War •Real-time strategy game • Released in 1998 by Blizzard • Three races • Protoss, Terran, Zerg • Play time • Several minutes ~ Hours • Goal of the game • Eliminate all the buildings of opponents Resource Management Uncertainty Handling Micro Management Decision Making Real-Time Response
  • 3.
    StarCraft AI Competition •Annual event since 2010 • Three independent competitions (IEEE CIG, AIIDE, and SSCAIT) • C++ or JAVA programming using BWAPI (Brood War API) • AI vs. AI matches • Fully automated tournament software • 8 days running with 17 machines
  • 4.
    Basic Rules AI1 AI2 AI4 AI5 AI3 •Full round-robin style tournament • 100 Rounds with 5 maps • File I/O is allowed • Used for long-term adaptation • 42 milliseconds response time requirement • 1 hour time limit for each match
  • 5.
    2016 Update onRules • Open source policy • All participants’ source code will be available after this competition • Introducing qualifying and final tournaments • Qualifying • Select top players (50%) to advance 2nd stage • Final • Full round-robin tournaments of the top players • Winner is determined from the 2nd Stage Qualification (All entries) Final (Half)
  • 6.
    Number of GamesPlayed 70 2340 8279 5579 10251 20788 40 4050 2500 4680 2730 14800 0 5000 10000 15000 20000 25000 2010 2011 2012 2013 2014 2015 2016 AIIDE CIG [Source] 2010~2015 data from https://webdocs.cs.ualberta.ca/~cdavid/starcraftaicomp/report2015.shtml
  • 7.
    Entrants • 16 participantsfrom 13 countries • 9 Updated or newcomer submissions • 7 Last year’s bot without change (Re-entrance) AIUR Bonjwa OpprimoBot Overkill Salsa TerranUAB UAlbertaBot Last Year’s bot (Re-entrance) LetaBot MegaBot SRbotOne XelnagaII ZiaBot Iron tscmoo Tyr ZZZKBot Newcomers & Updated
  • 8.
    Entrants (Details) Aiur Bonjwa OpprimoBot Overkill Salsa TerranUAB UAIbertaBot LetaBot MegaBot SRbotOne XelnagaII ZiaBot (Navinad) Iron tscmoo Tyr ZZZKBot ProtossFlorian Richoux Dustin Dannenhauer Johan Hagelback Sijia Xu Pablo Garcia Sanchez Filip Bober David Churchill Martin Rooijackers Anderson Rocha Tavares Johan Kayser Cheong-mok Bae Sungguk Cha Igor Dimitrijevic Vegard Mella Simon Prins Chris Coxe Terran Terran Zerg Zerg Terran Random Terran Protoss Terran Protoss Zerg Terran Terran Terran Zerg Université de Nantes Lehigh University Linnaeus University - University of Granada Poznan Univ. of Technology University of Alberta Maastricht University Universidade Federal de Minas UQAM Sejong University UNIST - - Utrecht University - - - - - - - - Student Student Student Student - - - Programmer SW Engineer/Developer
  • 9.
    Race Distribution 1 2 3 4 5 6 7 8 9 0 2013 20142015 2016 Zerg Terran Protoss Random
  • 10.
  • 11.
    Result – QualifyingStage Bot Iron Tscmoo LetaBot Overkill MegaBot UAlbertaBot ZZZKBot Aiur Tyr Ziabot TerranUAB SRbotOne OpprimoBot XelnagaII Bonjwa Salsa Race Games 1500 1498 1500 1499 1499 1499 1499 1498 1499 1497 1498 1499 1498 1497 1499 1497 Terran Terran Terran Zerg Protoss Random Zerg Protoss Terran Zerg Terran Terran Terran Protoss Terran Zerg Win 1188 1153 1111 1064 1051 1038 1037 946 924 695 502 332 331 310 284 22 Loss 312 345 389 435 448 461 462 552 575 802 996 1167 1167 1187 1215 1475 Win% 79.2 76.97 74.07 70.98 70.11 69.25 69.18 63.15 61.64 46.43 33.51 22.15 22.1 20.71 18.95 1.47 AvgTime 14:11 14:15 13:34 11:37 11:44 9:59 7:23 13:20 17:19 9:56 14:11 14:45 16:46 13:34 12:05 10:53 Hour 30 8 38 16 18 30 0 32 77 21 18 19 0 51 32 0 Crash 22 27 15 22 102 0 0 7 25 183 72 3 204 677 1 480 Timeout 7 0 0 0 4 0 0 0 0 114 1 6 0 226 0 119 Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 - - 11988 11988 11988 - 12:51 195 1840 477Total
  • 12.
    0 10 20 30 40 50 60 70 80 90 100 0 10 2030 40 50 60 70 80 90 100 WinRate Round Number Qualification: Win Ratio Over Time Iron tscmoo LetaBot Overkill MegaBot UAlbertaBot ZZZKBot Aiur Tyr Ziabot TerranUAB SRbotOne OpprimoBot XelnagaII Bonjwa Salsa
  • 13.
    Result – FinalStage Bot Tscmoo Iron LetaBot ZZZKBot Overkill UAlbertaBot MegaBot Aiur Race Games 700 700 700 699 700 699 700 700 Terran Terran Zerg Random Protoss Win 456 381 376 371 360 343 266 246 Loss 244 319 324 328 340 356 434 454 Win% 65.14 54.43 53.71 53.08 51.43 49.07 38.00 35.14 AvgTime 15:29 15:23 13:45 8:42 13:16 11:22 10:56 12:54 Hour 3 17 8 1 15 22 5 15 Crash 0 14 0 0 4 0 100 2 Timeout 0 3 0 0 0 1 6 0 Rank 1 2 3 4 5 6 7 8 - - 2799 2799 2799 - 12:43 43 120 10Total Terran Zerg Protoss Congratulation! Winner of 2016 IEEE CIG StarCraft AI Competition TSCMOO by Vegard Mella from Norway
  • 14.
  • 15.
    0 10 20 30 40 50 60 70 80 90 100 0 10 2030 40 50 60 70 80 90 100 WinRate Round Number Result - Stage2: Win Percentage Over Time tscmoo Iron LetaBot ZZZKBot Overkill UAlbertaBot MegaBot Aiur
  • 16.
    Winner Tscmoo • Comeback withTerran Bot (Last year: Zerg) • It’s good with vultures • Use neural network ‘Long Short-Term Memory (LSTM)’ for some high level decisions (which units to build) to provide hints to bunch of heuristics • Remember what happen in previous games, and do something reasonable in response next game Terran
  • 17.
    2nd Rank Iron • Asuccessor of “Stone”(Rank 19/22 in AIIDE 2015) • Multi-Agent System, each controlled unit is an Agent. (Agent behave to avoid blocking situations, indecision, predictability.) • Iron’s unis have simple behaviors like “harass his main” or “keep alive” Terran
  • 18.
    3rd Rank LetaBot • UseA* and DFS algorithm to find a build place for block choke point (set up barricade) • Use pathfinding algorithm for efficient resource gathering • Use Influence map to calculate units’ attack power • Resource gathering algorithm based on linear algebra Terran
  • 19.
    7th Rank MegaBot • Proof-of-Conceptbot that plays the strategy selection Reference: To appear in AIIDE 2016 Tavares, Azpurua, dos Santos, Chaimowicz.“Rock, Paper, StarCraft: Strategy Selection in Real-time Strategy Games.” • Use codes of Skynet, Xelnaga, and NUSBot • Select strategy at the start phase through modified epsilon-greedy 𝑉 𝑠, 𝑜 ← 1 − 𝛼 ∗ 𝑉 𝑠, 𝑜 + 𝛼 ∗ 𝑟𝑒𝑠𝑢𝑙𝑡 protoss
  • 20.
  • 21.
    Acknowledgements David Churchill (University ofAlberta) Organizer of AIIDE StarCraft AI Competition Michal Certicky and his team members (Czech Technical University in Prague) Organizer of Student StarCraft AI Tournament
  • 22.