Alberto Marchesi, Francesco Trovò, Nicola Gatti 0001. Learning Probably Approximately Correct Maximin Strategies in Simulation-Based Games with Infinite Strategy Spaces. In Amal El Fallah-Seghrouchni, Gita Sukthankar, Bo An 0001, Neil Yorke-Smith, editors, Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS '20, Auckland, New Zealand, May 9-13, 2020. pages 834-842, International Foundation for Autonomous Agents and Multiagent Systems, 2020. [doi]
@inproceedings{MarchesiT020,
title = {Learning Probably Approximately Correct Maximin Strategies in Simulation-Based Games with Infinite Strategy Spaces},
author = {Alberto Marchesi and Francesco Trovò and Nicola Gatti 0001},
year = {2020},
url = {https://dl.acm.org/doi/abs/10.5555/3398761.3398860},
researchr = {https://researchr.org/publication/MarchesiT020},
cites = {0},
citedby = {0},
pages = {834-842},
booktitle = {Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS '20, Auckland, New Zealand, May 9-13, 2020},
editor = {Amal El Fallah-Seghrouchni and Gita Sukthankar and Bo An 0001 and Neil Yorke-Smith},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
isbn = {978-1-4503-7518-4},
}