@article{pita2009using,
  title={Using game theory for Los Angeles airport security},
  author={Pita, James and Jain, Manish and Ord{\'o}nez, Fernando and Portway, Christopher and Tambe, Milind and Western, Craig and Paruchuri, Praveen and Kraus, Sarit},
  journal={AI magazine},
  volume={30},
  number={1},
  pages={43--43},
  year={2009}
}

@inproceedings{shieh2012protect,
  title={Protect: A deployed game theoretic system to protect the ports of the united states},
  author={Shieh, Eric and An, Bo and Yang, Rong and Tambe, Milind and Baldwin, Craig and DiRenzo, Joseph and Maule, Ben and Meyer, Garrett},
  booktitle={Proceedings of the 11th international conference on autonomous agents and multiagent systems-volume 1},
  pages={13--20},
  year={2012}
}

@article{duan2021stochastic,
  title={Stochastic strategies for robotic surveillance as stackelberg games},
  author={Duan, Xiaoming and Paccagnan, Dario and Bullo, Francesco},
  journal={IEEE Transactions on Control of Network Systems},
  volume={8},
  number={2},
  pages={769--780},
  year={2021},
  publisher={IEEE}
}

@article{duan2019markov,
  title={Markov chains with maximum return time entropy for robotic surveillance},
  author={Duan, Xiaoming and George, Mishel and Bullo, Francesco},
  journal={IEEE Transactions on Automatic Control},
  volume={65},
  number={1},
  pages={72--86},
  year={2019},
  publisher={IEEE}
}

@article{sarig2009lecture,
  title={Lecture notes on ergodic theory},
  author={Sarig, Omri},
  journal={Lecture Notes, Penn. State University},
  year={2009}
}

@article{basilico2022recent,
  title={Recent trends in robotic patrolling},
  author={Basilico, Nicola},
  journal={Current Robotics Reports},
  volume={3},
  number={2},
  pages={65--76},
  year={2022},
  publisher={Springer}
}

@article{tamilselvan2024exploring,
  title={Exploring the ingredients, mixtures, and inclinations of geopolitical risk},
  author={Tamilselvan, M and Halder, Abhishek and Kannadhasan, M},
  journal={International Review of Economics \& Finance},
  volume={90},
  pages={187--206},
  year={2024},
  publisher={Elsevier}
}

@article{pursiainen2023european,
  title={From European critical infrastructure protection to the resilience of European critical entities: what does it mean?},
  author={Pursiainen, Christer and Kyt{\"o}maa, Eero},
  journal={Sustainable and Resilient Infrastructure},
  volume={8},
  number={sup1},
  pages={85--101},
  year={2023},
  publisher={Taylor \& Francis}
}


@article{bueger2023critical,
  title={Critical maritime infrastructure protection: What’s the trouble?},
  author={Bueger, Christian and Liebetrau, Tobias},
  journal={Marine policy},
  volume={155},
  pages={105772},
  year={2023},
  publisher={Elsevier}
}


@article{john2023rosso,
  title={{RoSSO: A High-Performance Python Package for Robotic Surveillance Strategy Optimization Using JAX}},
  author={John, Yohan and Hughes, Connor and Diaz-Garcia, Gilberto and Marden, Jason R and Bullo, Francesco},
  journal={arXiv preprint arXiv:2309.08742},
  year={2023}
}
@inproceedings{aamas09,
author = {Basilico, Nicola and Gatti, Nicola and Amigoni, Francesco},
title = {Leader-Follower Strategies for Robotic Patrolling in Environments with Arbitrary Topologies},
year = {2009},
isbn = {9780981738161},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
address = {Richland, SC},
abstract = {Game theoretic approaches to patrolling have become a topic of increasing interest in the very last years. They mainly refer to a patrolling mobile robot that preserves an environment from intrusions. These approaches allow for the development of patrolling strategies that consider the possible actions of the intruder in deciding where the robot should move. Usually, it is supposed that the intruder can hide and observe the actions of the patroller before intervening. This leads to the adoption of a leader-follower solution concept. In this paper, mostly theoretical in its nature, we propose an approach to determine optimal leader-follower strategies for a mobile robot patrolling an environment. Differently from previous works in literature, our approach can be applied to environments with arbitrary topologies.},
booktitle = {Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1},
pages = {57–64},
numpages = {8},
keywords = {leader-follower strategies, robotic patrolling},
location = {Budapest, Hungary},
series = {AAMAS '09}
}

@article{AIJ2023,
title = {Solving zero-sum one-sided partially observable stochastic games},
journal = {Artificial Intelligence},
volume = {316},
pages = {103838},
year = {2023},
issn = {0004-3702},
doi = {https://doi.org/10.1016/j.artint.2022.103838},
url = {https://www.sciencedirect.com/science/article/pii/S0004370222001783},
author = {Karel Horák and Branislav Bošanský and Vojtěch Kovařík and Christopher Kiekintveld},
keywords = {Zero-sum partially observable stochastic games, One-sided information, Value iteration, Heuristic search value iteration},
abstract = {Many real-world situations are dynamic, with long-term interactions between multiple agents with uncertainty and limited observations. The agents must reason about which actions to take while also predicting and learning about what actions the other agents will take and how their choices will interact. In the most general setting, there is no limitation on the length of the sequence of actions the agent can perform — that is, there is no fixed horizon that can be used as an endpoint for analysis. These settings can be modeled as partially observable stochastic games (POSGs). Many adversarial domains (e.g., security settings) can be modeled as strictly competitive (or zero-sum) variants of these games. While these models are capable of modeling a wide variety of realistic problems, solving general POSGs is computationally intractable, so we focus on a broad subclass of POSGs called one-sided POSGs. In these games, only one agent has imperfect information while their opponent has full knowledge of the current situation. We provide a complete approach for solving zero-sum, one-sided POSGs: we (1) give a theoretical analysis of one-sided POSGs and their value functions, (2) show that a variant of a value-iteration algorithm converges in this setting, (3) adapt the heuristic search value-iteration algorithm for solving one-sided POSGs, (4) describe how to use approximate value functions to derive strategies in the game, and (5) experimentally demonstrate that our algorithm can solve one-sided POSGs of non-trivial sizes and analyze the scalability of our algorithm in three different domains: pursuit-evasion, patrolling, and search games.}
}


@inproceedings{ICAPS2014,
  author       = {Yevgeniy Vorobeychik and
                  Bo An and
                  Milind Tambe and
                  Satinder Singh},
  editor       = {Steve A. Chien and
                  Minh Binh Do and
                  Alan Fern and
                  Wheeler Ruml},
  title        = {Computing Solutions in Infinite-Horizon Discounted Adversarial Patrolling
                  Games},
  booktitle    = {Proceedings of the Twenty-Fourth International Conference on Automated
                  Planning and Scheduling, {ICAPS} 2014, Portsmouth, New Hampshire,
                  USA, June 21-26, 2014},
  publisher    = {{AAAI}},
  year         = {2014},
  url          = {http://www.aaai.org/ocs/index.php/ICAPS/ICAPS14/paper/view/7783},
  timestamp    = {Tue, 19 Apr 2022 16:03:29 +0200},
  biburl       = {https://dblp.org/rec/conf/aips/VorobeychikATS14.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@article{lanctot2023population,
  title={Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning},
  author={Lanctot, Marc and Schultz, John and Burch, Neil and Smith, Max Olan and Hennes, Daniel and Anthony, Thomas and Perolat, Julien},
  journal={arXiv preprint arXiv:2303.03196},
  year={2023}
}

@inproceedings{sinha2018stackelberg,
  title={Stackelberg security games: Looking beyond a decade of success},
  author={Sinha, Arunesh and Fang, Fei and An, Bo and Kiekintveld, Christopher and Tambe, Milind},
  booktitle={IJCAI},
  year={2018},
  organization={IJCAI}
}

@inproceedings{letchford2013solving,
  title={Solving security games on graphs via marginal probabilities},
  author={Letchford, Joshua and Conitzer, Vincent},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={27},
  pages={591--597},
  year={2013}
}

@book{norris1998markov,
  title={Markov chains},
  author={Norris, James R},
  year={1998},
  publisher={Cambridge university press}
}

@article{barabasi1999emergence,
  title={Emergence of scaling in random networks},
  author={Barab{\'a}si, Albert-L{\'a}szl{\'o} and Albert, R{\'e}ka},
  journal={Science},
  volume={286},
  number={5439},
  pages={509--512},
  year={1999},
  publisher={American Association for the Advancement of Science}
}

@article{erdds1959random,
  title={On random graphs I.},
  author={Erd{\H{o}}s, Paul and R{\'e}nyi, Alfr{\'e}d},
  journal={Publ. Math. Debrecen},
  volume={6},
  pages={290--297},
  year={1959}
}

@article{watts1998collective,
  title={Collective dynamics of ‘small-world’ networks},
  author={Watts, Duncan J and Strogatz, Steven H},
  journal={Nature},
  volume={393},
  number={6684},
  pages={440--442},
  year={1998},
  publisher={Nature Publishing Group}
}