Trade-Offs in Sampling-Based Adversarial Planning
暂无分享,去创建一个
[1] Bart Selman,et al. Understanding Sampling Style Adversarial Search Methods , 2010, UAI.
[2] David Silver,et al. Combining online and offline knowledge in UCT , 2007, ICML '07.
[3] David Silver,et al. Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (2008) Achieving Master Level Play in 9 × 9 Computer Go , 2022 .
[4] Judea Pearl,et al. On the Nature of Pathology in Game Searching , 1983, Artif. Intell..
[5] Ryan B. Hayward,et al. Monte Carlo Tree Search in Hex , 2010, IEEE Transactions on Computational Intelligence and AI in Games.
[6] Emden R. Gansner,et al. An open graph visualization system and its applications to software engineering , 2000 .
[7] Bart Selman,et al. On Adversarial Search Spaces and Sampling-Based Planning , 2010, ICAPS.
[8] Ivan Bratko,et al. When is it better not to look ahead? , 2010, Artif. Intell..
[9] Csaba Szepesvári,et al. Bandit Based Monte-Carlo Planning , 2006, ECML.
[10] Richard J. Lorentz. Amazons Discover Monte-Carlo , 2008, Computers and Games.
[11] Rémi Coulom,et al. Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search , 2006, Computers and Games.
[12] Alan Fern,et al. UCT for Tactical Assault Planning in Real-Time Strategy Games , 2009, IJCAI.
[13] Rémi Munos,et al. Bandit Algorithms for Tree Search , 2007, UAI.
[14] Peter Auer,et al. Finite-time Analysis of the Multiarmed Bandit Problem , 2002, Machine Learning.
[15] Yngvi Björnsson,et al. Simulation-Based Approach to General Game Playing , 2008, AAAI.
[16] Dana S. Nau,et al. An Investigation of the Causes of Pathology in Games , 1982, Artif. Intell..
[17] Mark H. M. Winands,et al. Evaluation Function Based Monte-Carlo LOA , 2009, ACG.