Due to Google closing Google Code, this project has moved to GitHub: https://github.com/santiontanon/microrts

microRTS is a small implementation of an RTS game, designed to perform AI research. The advantage of using microRTS with respect to using a full-fledged game like Wargus or Starcraft (using BWAPI) is that microRTS is much simpler, and can be used to quickly test theoretical ideas, before moving on to full-fledged RTS games.

microRTS is deterministic and real-time (i.e. players can issue actions simultaneously, and actions are durative). It is possible to experiment both with fully-observable and partially-observable games. Thus, it is not adequate for evaluating AI techniques designed to deal with non-determinism (although future versions of microRTS might include non-determinism activated via certain flags). As part of the implementation, I include a collection of hard-coded, and game-tree search techniques (such as variants of minimax, Monte Carlo search, and Monte Carlo Tree Search).

microRTS was developed by Santiago Ontañón. A precompiled version for demonstration purposes can be found here microRTS.zip (although this is an old version, for the latest version please use the subversion repository)

For a video of how microRTS lookslike when a human plays see youtube video

To cite microRTS, please cite this paper:

Santiago Ontañón (2013) The Combinatorial Multi-Armed Bandit Problem and its Application to Real-Time Strategy Games, In AIIDE 2013. pp. 58 - 64.

Contributions: * The LSI AI was contributed by Alexander Shleyfman, Antonin Komenda and Carmel Domshlak (the theory behind the AI is described in this paper. * A separate branch of this project is maintained by Jeff Bernard and Brian Magerko (at http://code.google.com/p/micrortsx/ ), focusing on a version more suitable for doing competitions amongst students. Some features (like EntityType class) have been borrowed from that branch, and incorporated back into the main branch here.

Instructions: