Marius Stanescu
Title
Cited by
Cited by
Year
Evaluating Real-Time Strategy Game States Using Convolutional Neural Networks
M Stanescu, NA Barriga, A Hess, M Buro
IEEE Computational Intelligence in Games 2016, 2016
482016
Predicting army combat outcomes in StarCraft
M Stanescu, SP Hernandez, G Erickson, R Greiner, M Buro
Proceedings of the AAAI Conference on Artificial Intelligence and …, 2013
442013
Combining strategic learning with tactical search in real-time strategy games
N Barriga, M Stanescu, M Buro
Proceedings of the AAAI Conference on Artificial Intelligence and …, 2017
362017
Hierarchical adversarial search applied to real-time strategy games
M Stanescu, N Barriga, M Buro
Proceedings of the AAAI Conference on Artificial Intelligence and …, 2014
352014
Game tree search based on nondeterministic action scripts in real-time strategy games
NA Barriga, M Stanescu, M Buro
IEEE Transactions on Games 10 (1), 69-77, 2017
322017
Puppet search: Enhancing scripted behavior by look-ahead search with applications to real-time strategy games
N Barriga, M Stanescu, M Buro
Proceedings of the AAAI Conference on Artificial Intelligence and …, 2015
282015
Using Lanchester attrition laws for combat prediction in StarCraft
M Stanescu, N Barriga, M Buro
Proceedings of the AAAI Conference on Artificial Intelligence and …, 2015
232015
Predicting Opponent’s Production in Real-Time Strategy Games with Answer Set Programming
M Stanescu, M Certicky
IEEE Transactions on Computational Intelligence and AI in Games, 2014
232014
Building Placement Optimization in Real-Time Strategy Games
NA Barriga, M Stanescu, M Buro
Tenth Annual AAAI Conference on Artificial Intelligence and Interactive …, 2014
162014
Parallel UCT search on GPUs
NA Barriga, M Stanescu, M Buro
2014 IEEE Conference on Computational Intelligence and Games, 1-7, 2014
122014
Rating systems with multiple factors
M Stanescu
Master's thesis, School of Informatics, Univ. of Edinburgh, Edinburgh, UK, 2011
112011
Improving rts game ai by supervised policy learning, tactical search, and deep reinforcement learning
NA Barriga, M Stanescu, F Besoain, M Buro
IEEE Computational Intelligence Magazine 14 (3), 8-18, 2019
92019
Introducing Hierarchical Adversarial Search, a Scalable Search Procedure for Real-Time Strategy Games
M Stanescu, NA Barriga, M Buro
21st European Conference on Artificial Intelligence 263, 1099 - 1100, 2014
72014
Combining scripted behavior with game tree search for stronger, more robust game AI
NA Barriga, M Stanescu, M Buro
Game AI Pro 3: Collected Wisdom of Game AI Professionals, 179, 2017
62017
Combat outcome prediction for real-time strategy games
M Stanescu, NA Barriga, M Buro
Game AI Pro 3: Collected Wisdom of Game AI Professionals, 301, 2017
42017
Outcome Prediction and Hierarchical Models in Real-Time Strategy Games
M Stanescu
PhD Thesis, University of Alberta, Canada, 2019
12019
Spatial Action Decomposition Learning Applied to RTS Combat Games
M Stanescu, M Buro
Proceedings of the AIIDE 2018 Workshop on Artificial Intelligence for …, 2018
12018
The Quo Vadis submission at Traffic4cast 2019
D Oneata, CG Alexandru, M Stanescu, O Pascu, A Magan, A Postelnicu, ...
arXiv preprint arXiv:1910.12363, 2019
2019
Improving RTS Game AI by Supervised Policy Learning, Tactical Search, and Deep Reinforcement Learning
M Stanescu, M Buro
Hierarchical Adversarial Search and its Application to Real-Time Strategy Games
M Stanescu, NA Barriga, M Buro
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