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.
For a video of how microRTS looks like when a human plays see a youtube video
An AI competition was organized aroung microRTS in the IEEE-CIG 2017 conference, and again in 2018. For more information on the competition see the competition website
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.
The LSI AI was contributed by Alexander Shleyfman, Antonin Komenda and Carmel Domshlak (the theory behind the AI is described in this paper.
