@inproceedings{21b9f9a838094aacb570ba47823f8e4b,
title = "Integration of deterministic inference with formal synthesis for control under uncertainty",
abstract = "In this work, we consider an agent playing a turn-based game in a known environment against an adversary with unknown dynamics. The model of the adversary is assumed to belong to a subclass of regular languages that can be learned in the limit. We use tools from formal methods to synthesize a control strategy for the agent to win the game as it learns the model of its adversary, if a winning strategy exists. The strategy is updated as new information about the adversary is learned. The proposed framework is tested in simulation.",
author = "Leahy, {Kevin J.} and Prasanna Kannappan and Adam Jardine and Herbert Tanner and Jeffrey Heinz and Calin Belta",
note = "Funding Information: This work was partially supported by NSF CNS-1035588 at Boston University Publisher Copyright: {\textcopyright} 2016 American Automatic Control Council (AACC).; 2016 American Control Conference, ACC 2016 ; Conference date: 06-07-2016 Through 08-07-2016",
year = "2016",
month = jul,
day = "28",
doi = "10.1109/ACC.2016.7526117",
language = "English (US)",
series = "Proceedings of the American Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4829--4834",
booktitle = "2016 American Control Conference, ACC 2016",
address = "United States",
}