@article{Moraes_Lelis_2018, title={Asymmetric Action Abstractions for Multi-Unit Control in Adversarial Real-Time Games}, volume={32}, url={https://ojs.aaai.org/index.php/AAAI/article/view/11432}, DOI={10.1609/aaai.v32i1.11432}, abstractNote={ <p> Action abstractions restrict the number of legal actions available during search in multi-unit real-time adversarial games, thus allowing algorithms to focus their search on a set of promising actions. Optimal strategies derived from un-abstracted spaces are guaranteed to be no worse than optimal strategies derived from action-abstracted spaces. In practice, however, due to real-time constraints and the state space size, one is only able to derive good strategies in un-abstracted spaces in small-scale games. In this paper we introduce search algorithms that use an action abstraction scheme we call asymmetric abstraction. Asymmetric abstractions retain the un-abstracted spaces’ theoretical advantage over regularly abstracted spaces while still allowing the search algorithms to derive effective strategies, even in large-scale games. Empirical results on combat scenarios that arise in a real-time strategy game show that our search algorithms are able to substantially outperform state-of-the-art approaches. </p> }, number={1}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Moraes, Rubens and Lelis, Levi}, year={2018}, month={Apr.} }