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A curated list of resources dedicated to StarCraft: Brood War AI
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README.md

Awesome Brood War AI

In this repository, you will find many:

  1. API & Extensions
  2. Bots
  3. Competitions
  4. Papers
  5. Others

If you have any suggests or comments, just pull requests.

Just enjoy it!


API & Extensions

  • BWAPI [Link] [github] a free and open source C++ framework that is used to interact with the popular Real Time Strategy (RTS) game Starcraft: Broodwar.

    • BWMirror [Link] [github] [Document] BWMirror API is a Java wrapper for BWAPI.

    • JNIBWAPI [github] a Java interface for the Brood War API (BWAPI) using Java Native Interface

    • CyBW [bitbucket] CyBW is a Python language wrapper for BWAPI implemented in Cython.

    • GOAL [Link]

Extensions/Addons

  • BWEM [Link] Brood War Easy Map is a C++ library that analyses Brood War's maps and provides relevant information such as areas, choke points and base locations.

  • BWTA [Link] Broodwar Terrain Analyzer (BWTA) is a add-on for BWAPI which analyzes the current starcraft map and returns the set of expansion locations, regions, and choke points.

  • BWTA2 [Link] [Wiki] BWTA2 is a fork of BWTA, an add-on for BWAPI that analyzes the map and computes the regions, chokepoints, and base locations.

  • SparCraft [git-wiki] SparCraft is an open source StarCraft combat simulation package.

  • Boss [git-wiki] The StarCraft Build Order Search System (BOSS) is a StarCraft: BroodWar build order search and simulation package used to plan all build orders in UAlbertaBot.

  • DropLauncher A BWAPI bot launcher for human vs bot games. [github]

Bots

Competitions

Papers

https://github.com/SKTBrain/awesome-starcraftAI

https://github.com/bwapi/bwapi/wiki/Academics

https://github.com/Eric-Wallace/starcraft-research-papers

Research Papers

Surveys

  • S. Ontañón, G. Synnaeve, A. Uriarte, F. Richoux, D. Churchill, M. Preuss, A survey of real-time strategy game ai research and competition in starcraft, IEEE TCIAIG, 2013. [Survey]
  • S. Ontañón, G. Synnaeve, A. Uriarte, F. Richoux, D. Churchill, M. Preuss, RTA AI Problems and Techniques, Springer Encyclopedia of Computer Graphics and Games, 2015. [Survey]
  • D. Churchill, M. Preuss, F. Richoux, G. Synnaeve, A. Uriarte, S. Ontañón, M. Certický, StarCraft Bots and Competitions, Springer Encyclopedia of Computer Graphics and Games, 2016. [Survey]
  • R. Lara-Cabrera, C. Cotta, A. Fernandez-Leiva, A review of computational intelligence in RTS games, IEEE FOCI, 2013. [Survery]

Benchmark

  • A. Uriarte, S. Ontãñón, A Benchmark for StarCraft Intelligent Agents, AAAI AIIDE, 2015. [Paper]

Thesis

  • G. Synnaeve, Bayesian programming and learning for multi-player video games: application to RTS AI, Ph.D. Thesis, INPG, 2012. [Thesis]
  • J. Hagelback, Multi-Agent Potential Field Based Architectures for Real-Time Strategy Game Bots, Ph.D. Thesis, BIT, 2012. [Thesis]
  • D. Churchill, Heuristic Search Techniques for Real-Time Strategy Games, Ph.D. Thesis, U. Alberta, 2016. [Thesis]

Dataset

  • G. Synnaeve, P. Bessiere, A Dataset for StarCraft AI & an Example of Armies Clustering, arXiv, 2012. [Paper]
  • G. Robertson, I. Watson, An Improved Dataset and Extraction Process for Starcraft AI, FLAIRS, 2014. [Paper]
  • Z. Lin, J. Gehring, V. Khalidov, G. Synnaeve, STARDATA: A StarCraft AI Research Dataset, arXiv, 2017. [Paper]

Bayesian Approach

  • G. Synnaeve, P. Bessiere, A bayesian model for opening prediction in rts games with application to starcraft, IEEE CIG, 2011. [Paper]
  • G. Synnaeve, P. Bessiere, A Bayesian model for RTS units control applied to StarCraft, IEEE CIG, 2011. [Paper]
  • G. Synnaeve, P. Bessiere, Special tactics: A bayesian approach to tactical decision-making, IEEE CIG, 2012. [Paper]

Satisfaction and Optimization

  • M. Certický, Implementing a Wall-In Building Placement in StarCraft with Declarative Programming, arXiv, 2013. [Paper]
  • J. Fradin, F. Richoux, Robustness and Flexibility of GHOST, AIIDE Third Workshop on Artificial Intelligence in Adversarial Real-Time Games, 2015. [Paper]
  • F. Richoux, A. Uriarte, J.-F. Baffier, GHOST: A Combinatorial Optimization Framework for Real-Time Problems, IEEE TCIAIG, 2016. [Paper]
  • F. Richoux, A. Uriarte, S. Ontañón, Walling in Strategy Games via Constraint Optimization, AAAI AIIDE, 2014. [Paper]

Planning

  • B. Weber. M. Mateas, Case-Based Reasoning for Build Order in Real-Time Strategy Games, AAAI AIIDE, 2009. [Paper]
  • B. Weber, M. Mateas, A. Jhala, Applying Goal-Driven Autonomy to StarCraft, AAAI AIIDE, 2010. [Paper]
  • D. Churchill, M. Buro, Build Order Optimization in StarCraft, AAAI AIIDE, 2011. [Paper]
  • D. Churchill, M. Buro, Incorporating Search Algorithms into RTS Game Agents, AAAI AIIDE Workshop, 2012. [Paper]
  • M. Stanescu, N. Barriga, M. Buro, Hierarchical Adversarial Search Applied to Real-Time Strategy Games, AAAI AIIDE, 2014. [Paper]
  • N. Justesen, S. Risi, Continual Online Evolutionary Planning for In-Game Build Order Adaptation in StarCraft, ACM GECCO, 2017. [Paper]

Prediction

  • B. Weber, M. Mateas, A Data mining approach to strategy prediction, IEEE CIG, 2009. [Paper]
  • H. Park, H. Cho, K. Lee, K. Kim, Prediction of Early Stage Opponents Strategy for StarCraft AI using Scouting and Machine Learning, Workshop at SIGGRAPH Asia, 2012. [Paper]
  • H. Cho, K. Kim, S. Cho, Replay-based Strategy Prediction and Build Order Adaptation for StarCraft AI Bots, IEEE CIG, 2013. [Paper]
  • M. Stanescu, S. Hernandez, G. Erickson, R. Greiner, M. Buro, Predicting Army Combat Outcomes in StarCraft, AAAI AIIDE, 2013. [Paper]
  • Y. N. Ravari, S. Bakkes, P. Spronck, StarCraft Winner Prediction, AAAI AIIDE, 2016. [Paper]

Control

  • B. Weber, M. Mateas, A. Jhala, A Particle Model for State Estimation in Real-Time Strategy Games, AAAI AIIDE, 2011. [Paper]
  • A. Shantia, E. Begue, M. Wiering, Connectionist Reinforcement Learning for Intelligent Unit Micro Management in StarCraft, IJCNN, 2011. [Paper]
  • D. Churchill, A. Saffidine, M. Buro, Fast Heuristic Search for RTS Game Combat Scenarios, AAAI AIIDE, 2012. [Paper]
  • D. Churchill, M. Buro, Incorporating Search Algorithms into RTS Game Agents, AAAI AIIDE Workshop, 2012. [Paper]
  • S. Wender, I. Watson, Applying Reinforcement Learning to Small Scale Combat in the Real-Time Strategy Game StarCraft: Broodwar, IEEE CIG, 2012. [Paper]
  • D. Churchill, M. Buro, Portfolio Greedy Search and Simulation for Large-Scale Combat in StarCraft, IEEE CIG, 2013. [Paper]
  • K. Nguyen, Z. Wang, R. Thawonmas, Potential Flows for Controlling Scout Units in StarCraft, IEEE CIG, 2013. [Paper]
  • N. Justesen, S. Risi, Script-and Cluster-Based UCT for StarCraft, IEEE CIG, 2014. [Paper]
  • N. Usunier, G. Synnaeve, Z. Lin, S. Chintala, Episodic Exploration for Deep Deterministic Policies: an Application to StarCraft Micromanagement Tasks, arXiv, 2016. [arXiv] [ICLR 2017 Submission]

Full Game Play

  • B. Weber, M. Mateas, A. Jhala, Building Human-Level AI for Real-Time Strategy Games, AAAI ACS 2011. [Paper]
  • J. Young, F. Smith, C. Atkinson, K. Poyner, T. Chothia, SCAIL: An integrated Starcrat AI system, IEEE CIG, 2012. [Paper]

Learning from Demonstration

  • B. Weber, S. Ontañón, Using Automated Replay Annotation for Case-Based Planning in Games, ICCBR-Games Workshop, 2010. [Paper]
  • B. Weber, M. Mateas, A. Jhala, Learning from Demonstration for Goal-Driven Autonomy, AAAI, 2012. [Paper]
  • J. Young, N. Hawes, Learning Micro-Management Skills in RTS Games by Imitating Experts, AAAI AIIDE, 2014. [Paper]
  • N. Justesen, S. Risi, Learning Macromanagement in StarCraft from Replays using Deep Learning, IEEE CIG, 2017. [[Paper]](Learning Macromanagement in StarCraft from Replays using Deep Learning)

Miscellaneous

  • W. Gong, E. Lim, P. Achananuparp, F. Zhu, D. Lo, F. Chua, In-Game Action List Segmentation and Labeling in Real-Time Strategy Games, IEEE CIG, 2012. [Paper]
  • H. Alburg, F. Brynfors, F. Minges, B. Mattson, J. Svensson, Making and Acting on Predictions in StarCraft: Brood War, Bachelors Thesis, University of Gothenburg, 2014. [Theis]
  • M. Leece, A. Jhala, Sequential Pattern Mining in StarCraft: Brood War for Short and Long-Term Goals, AAAI AIIDE Workshop, 2014. [Paper]
  • G. Erickson, M. Buro, Global State Evaluation in StarCraft, AAAI AIIDE, 2014. [Paper]

Reports

  • J. Lewis, P. Trinh, D. Kirsh, A Corpus Analysis of Strategy Video Game Play in Starcraft: Brood War, COGSCI, 2011. [Paper]

  • M. Buro, D. Churchill, Real-Time Strategy Game Competitions, AI Magazine, 2012. [Report]

  • G. Robertson, I. Watson, A Review of Real-time Strategy Game AI, AI Magazine, 2014. [Report]

  • M. Kim, S. Kim, K. Kim, A. Dey, Evaluation of StarCraft Artificial Intelligence Competition Bots by Experienced Human Players, CHI, 2016. [Report]

  • M. Čertický, D. Churchill. The Current State of StarCraft AI Competitions and Bots. In Proceedings of the AIIDE 2017 Workshop on Artificial Intelligence for Strategy Games. 2017. [PDF]

  • D. Churchill, M. Preuss, F. Richoux, G. Synnaeve, A. Uriarte, S. Ontanón, M. Čertický. StarCraft Bots and Competitions. Chapter in Encyclopedia of Computer Graphics and Games (ECGG). Springer International Publishing. ISBN: 978-3-319-08234-9. 2016. [PDF]

  • A survey of real-time strategy game ai research and competition in starcraft. 2013. [PDF]

  • Multi-Agent Systems in StarCraft. H.J. Griffioen and D. Plenge. 2016. [PDF] A bechlor project based on GOAL, an agent programming language for programming cognitive agents. [GOAL]

Others

BWAI_Universities

Memorial University

Technische Universiteit Delft

University of Maastricht (Netherlands)

University of Southern California (USA)

Technical University of Denmark (Denmark)

https://cis.ieee.org/games-tc.html

http://www.starcraftai.com/wiki/StarCraft_AI_Benchmarks

[StarCraft: Brood War's Mechanics] Ctrl+F+Mechanics

[BW order timings]

[StarCraft WeaponType Data]

[StarCraft TechType Data]

[StarCraft UnitType Data]

[Unusual Unit Morphs]

https://www.researchgate.net/profile/Zhentao_Tang/publication/324686165_Recent_progress_of_deep_reinforcement_learningfrom_AlphaGo_to_AlphaGo_Zero/links/5adc9332a6fdcc29358aaa2a/Recent-progress-of-deep-reinforcement-learningfrom-AlphaGo-to-AlphaGo-Zero.pdf

TBD

https://zhuanlan.zhihu.com/p/29986506

https://zhuanlan.zhihu.com/p/35356234

http://www.starcraftai.com/wiki/StarCraft_AI_Benchmarks

http://www.starcraftai.com/wiki/StarCraft_Brood_War_Data_Mining

http://www.goliathdesigns.com/2011/02/starcraft_ai/

http://www.starcraftai.com/wiki/Why_not_StarCraft_2

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