Open Access
Issue |
MATEC Web Conf.
Volume 208, 2018
2018 3rd International Conference on Measurement Instrumentation and Electronics (ICMIE 2018)
|
|
---|---|---|
Article Number | 05003 | |
Number of page(s) | 6 | |
Section | Computer Science and Intelligent Technology | |
DOI | https://doi.org/10.1051/matecconf/201820805003 | |
Published online | 26 September 2018 |
- Buro, M. Call for AI research in RTS games. In Proceedings of the AAAI-04 Workshop on Challenges in Game AI (2004), pp.139–142. [Google Scholar]
- Ontañón, S., Synnaeve, G., Uriarte, A., Richoux, F., Churchill, D., & Preuss, M. (2013). A survey of real-time strategy game ai research and competition in starcraft. IEEE Transactions on Computational Intelligence & Ai in Games, 5(4), pp. 293–311. [CrossRef] [Google Scholar]
- Ontañón, S. Experiments with game tree search in real-time strategy games. Artif. Intell. 2012, arXiv:1208.1940. [Google Scholar]
- Chung, M., Buro, M., & Schaeffer, J. (2005). Monte Carlo Planning in RTS Games. IEEE Symposium on Computational Intelligence and Games (pp.117–124). DBLP. [Google Scholar]
- Balla, R.K.; Fern, A. UCT for tactical assault planning in real-time strategy games. In Proceedings of the 21st International Jont Conference on Artifical Intelligence; AAAI Press Palo Alto,, CA, USA, 2009; pp. 40–45. [Google Scholar]
- Churchill, D.; Saffidine, A.; Buro, M. Fast Heuristic Search for RTS Game Combat Scenarios. In Proceedings of the Artificial Intelligence and Interactive Digital Entertainment (AIIDE); AAAI Press: Palo Alto, CA, USA, 2012, pp. 112–117 [Google Scholar]
- Ontañón, S. The combinatorial multi-armed bandit problem and its application to real-time strategy games. In Proceedings of 9th Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE); AAAI Press: Palo Alto, CA, USA, 2013. [Google Scholar]
- Shleyfman A, Komenda A, Domshlak C. On Combinatorial Actions and CMABs with Linear Side Information[J]. Frontiers in Artificial Intelligence & Applications, 2014, 263:825–830. [Google Scholar]
- Buro, M. (2015). Adversarial hierarchical-task network planning for complex real-time games. International Conference on Artificial Intelligence (Vol.8, pp.1652–1658). AAAI Press. [Google Scholar]
- Kovarsky, A., & Buro, M. (2005). Heuristic search applied to abstract combat games. Lecture Notes in Computer Science, 3501, pp. 66–78. [CrossRef] [Google Scholar]
- TungDuc Nguyen, KienQuang Nguyen, & Ruck, T. (2015). Heuristic search exploiting non-additive and unit properties for rts-game unit micromanagement. Journal of Information Processing, 23(1), pp. 2–8. [CrossRef] [Google Scholar]
- Stanescu, M., Hernandez, S. P., Erickson, G., Greiner, R., & Buro, M. (2013). Predicting army combat outcomes in StarCraft. AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (pp.86–92). AAAI Press. [Google Scholar]
- Erickson, G., & Buro, M. (2014). Global state evaluation in StarCraft. Tenth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (pp.112–118). AAAI Press. [Google Scholar]
- Uriarte, A., & Ontañón, S. (2014). Game-tree search over high-level game states in RTS games. AIIDE. pp.73–79. [Google Scholar]
- Bakkes, S., Spronck, P., & Herik, J. V. D. (2013). Phase-dependent evaluation in rts games. [Google Scholar]
- Li, Y. J., Ng, P. H. F., & Shiu, S. C. K. (2015). A fast evaluation method for rts game strategy using fuzzy extreme learning machine. Natural Computing(3), pp. 1–13. [Google Scholar]
- Stanescu, M., Barriga, N. A., Hess, A., & Buro, M. (2017). Evaluating real-time strategy game states using convolutional neural networks. Computational Intelligence and Games. IEEE. [Google Scholar]
- Malik Ghallab, Dana Nau, Paolo Traverso. Automated Planning: Theory and Practice. 2008. Elsevier(Singapore) Pte.Ltd. [Google Scholar]
- Sacerdoti, E. D. (1975). The nonlinear nature of plans. International Joint Conference on Artificial Intelligence (pp.206–214). Morgan Kaufmann Publishers Inc. [Google Scholar]
- David Churchill. [D]. Heuristic Search Techniques for Real-Time Strategy Games. University of Alberta. 2016. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.