StarCraft Participants

Download

Binaries for all submissions are now available for download (part1, part2). Instructions for running.

UAlbertaBot

Affiliation: University of Alberta, Edmonton, Alberta, Canada (Computing Science Department)
Team Members: Michael Buro, David Churchill, Sterling Orsten, Jay Schmidek, Evan Farnsworth, Ian Morrison
Tournaments: 1, 2, 4
Race: Zerg
Website: http://www.cs.ualberta.ca/
Description:
A zerg bot with a few tricks up its sleeve.

 

HIJ

Affiliation: Finnish Meteorological Institute
Team Members: Ilja Honkonen
Tournaments:
4
Race:
Terran
Description:
Swarm intelligence using a fixed strategy
Download: Source

 

Sherbrooke

Affiliation: University of Sherbrooke
Team Members:
Anthony Jo Quinto (Anthony.Jo.Quinto@USherbrooke.ca), Steve Tousignant (Steve.Tousignant@USherbrooke.ca), Frederic St-Onge
Tournaments:
1, 2, 3
Description: Our bot uses primarily states machines to take decisions and it can recognize  the strategy of its opponent.

 

CONDENSER

Affiliation: Square-Enix Research Center
Team Members: Lingfeng Yang
Tournaments: 3, 4
Race: Terran
Description: This bot uses a probabilistic inference algorithms to drive higher-level strategy, with dynamic scripting being used for the lower levels.

 

botnik

Affiliation: Wayne State University, Detroit, MI, USA
Team Members: Paul S. McCarthy, Dr. Robert G. Reynolds
Tournaments:
3
Description: We used Cultural Algorithms to learn a build order for a Zealot Rush strategy.

 

ArixSheeBot

Affiliation: Tongji University
Team Members: Arix Shee(Lei Shi)
Tournaments: 1
Description: The robot is designed based on an aritificial neural network. It makes decision for the units by accessing informations of them and the enemy neasr them. There won't be a on-site training process because that will halt the program for a little while, so I just trained it at home and put those trained information in the memory for ANN to laod it at the begining.

 

krasi0

Affiliation: None
Team members:
Krasimir Krastev
Tournaments:
4
Race:
Terran
Description: The bot is using FSMs utilizing my knowledge of the game. 

 

Skynet

Affiliation: None
Team Members: Andrew Smith
Tournaments: 3, 4
Race: Protoss
Website: http://www.youtube.com/user/MrLaccolith

Description: A Protoss bot with a few strategies under its belt

 

 

JaReD

Affiliation: Dortmund University of Technology
Team Members: Jan Czogalla, Mike Preuss
Tournaments: 4
Race: Terran

 

Chronos

Affiliation: None
Team Members: Daan Bakker
Tournaments: 4
Race: Terran
Website: http://www.dbakker.com
Description: A Terran bot with some daring tactics.

 

BTHAI

Affiliation: Blekinge Institute of Technology, Sweden
Team members: Johan Hagelbäck
Tournaments: 4
Race: Terran
Website: http://code.google.com/p/bthai/
Description: A bot based on a modular multi-agent architecture with a combination of pathfinding and potential fields for navigating and engaging the enemy

 

sqlitebot

Affiliation: None
Team members: Jeremy Cothran
Tournaments: 4
Race: Terran
Website: http://code.google.com/p/sqlitebot/wiki/StarCraft
Description: a basic bot using recent activity/attraction points for massing troops

 

Manolobot

Affiliation: Artificial Intelligence R&D Laboratory - LIDIA. Universidad Nacional del Sur, Argentina
Team Members: Cristian Conde, Mariano Moreno, Diego Martinez
Tournaments: 4
Race: Terran
Website: http://code.google.com/p/manolobot/
Description: The bot uses low level IA algorithms to settle ground base for future development of high level planning.

 

AB3A

Affiliation: Instituto Superior Técnico (Technical University of Lisbon)
Team members: Tiago Henriques, Diogo Simões, David Antunes
Tournaments: 3, 4
Race: Protoss
Website: http://web.ist.utl.pt/~ist158634/ist/4.2/aasma/asap_bot.htm
Description: 3 Phase rush attack bot.

 

CIRGBot

Affiliation: National University of Ireland, Galway.
Team members: Nigel Burke
Tournaments: 3
Description: Protoss bot which uses state machines and influence maps

 

FreScBot

Affiliation: None
Team Members: Florent D'Halluin, Valentin Leon-Bonnet
Tournaments: 1, 2
Description: This is a simple micro bot based on a multi-agent + state machine model.
Download: Source

 

ZotBot

Affiliation: UC Irvine
Team Members: David Hirschberg
Tournaments: 4
Website: http://www.youtube.com/user/nwprtch?feature=mhum
Description: A Protoss bot using basic RTS rules to create advantages.

 

ItClusters

Affiliation: University of Novi Sad, Faculty of Technical Sciences
Team Members: Gajo Petrovic
Tournaments: 1, 3
Description: Bot uses a simple pre-made strategy of 19 steps, after which it uses a simple FSM in order to pick the build order. As for attacking, it just waits until enough units are made and  then sends them to attack. Doesn't build expansions or defenses.

 

MSAILBOAT

Affiliation: Michigan Student Artificial Intelligence Laboratory, University of Michigan-Ann Arbor
Team Members: Kevin Shih, Jason Long, Sean Zimmerman, Adam Kidder, Steve Wishnousky, Samantha Luber, Kevin Meyer
Tournaments: 1
Website: http://eecs.umich.edu/msail/
Description: State-based micromangement AI.

 

UTPA Bronc Script

Affiliation: University of Texas-Pan American
Team member: Jose Dimas
Tournament: 1
Description: Script designed as a introduction to the Artificial Intelligence. Designed to recognize units being used and execute a simple strategy.

 

Overmind

Affiliation: UC Berkeley
Team Members: David Burkett, David Hall, Taylor Berg-Kirkpatrick, John DeNero, Nick Hay, Haomiao Huang, Eugene Ma, Yewen Pu, Jie Tang, Dan Klein
Tournaments: 4
Race: Zerg
Website: http://overmind.cs.berkeley.edu, nlp.cs.berkeley.edu
Description: The Overmind uses a variety of AI techniques for decisions at various levels of abstraction.

 

Omega

Affiliation: None
Team Members: Olivier Gaça
Tournaments: 4
Race: Protoss
Description: The bot is an adaptive AI with its own building management written in F#.

 

BroodwarBotQ

Affiliation: INRIA Rhône-Alpes (France)
Team members: Gabriel Synnaeve
Tournaments: 1, 3
Description: A bot using FSM + Bayesian Programming for micro-manageement: meaning that in some states, the unit takes probabilistic decisions whereas what to do. Hard (FSM-like) states should be deprecated in favor of probabilistic states.
Website: http://github.com/SnippyHolloW/BroodwarBotQ

 

BuggyBugs

Affiliation: None
Team Members: Chris Strong
Tournaments: 4
Race: Zerg
Description: This was intended to be a hierachical series of state machines capturing behavior at various levels of cooperation.  However, time constraints have only permitted about 20% of the design to be implemented.  Most of the rest is taken from preliminary code exploring individual unit based context, stateless behavior and a thin layer of strategic code. There has not been adequate time for decent integration and testing.  The result is ... buggy bugs. 

 

SimpleToss

Affiliation: None
Team Members: Josh Hildebrand
Tournaments: 4
Race: Protoss
Description: Attempted use of bwsal for a protoss bot, though bwsal crashes a fair amount without any added code so here's hopin they'll update that great project again.

 

Mimic Bot

Affiliation: Rensselaer Polytechnic Institute (RPI)
Team Members: Luke Perkins
Tournaments: 3
Description: Mimic Bot mimics its opponent's build order, gaining an economic advantage whenever possible.

 

windbot

Affiliation: Tongji University
Team members: Peter Pan
Tournaments: 1
Website: http://www.hawkwithwind.net
Description: A simple micro controlling bot, developed with genetic programming. It gives estimated value for several order candidates and chooses the best one accroding to the trainning results.

 

MassExpand

Affiliation: None
Team Members: Ben Haanstra, Armon Toubman
Tournaments: 4
Race: Zerg
Website: http://www.armontoubman.com/scai
Description: Ideas based on self-organising systems and emergence. Adaptive buildsystem, albeit some choices were hardcoded for simplicity. Units use decision trees for micromanagement.