Encoding human behavior in information design through deep learning

G Yu, W Tang, S Narayanan… - Advances in Neural …, 2024 - proceedings.neurips.cc
We initiate the study of $\textit {behavioral information design} $ through deep learning. In
information design, a $\textit {sender} $ aims to persuade a $\textit {receiver} $ to take certain …

Airsim-w: A simulation environment for wildlife conservation with uavs

E Bondi, D Dey, A Kapoor, J Piavis, S Shah… - Proceedings of the 1st …, 2018 - dl.acm.org
Increases in poaching levels have led to the use of unmanned aerial vehicles (UAVs or
drones) to count animals, locate animals in parks, and even find poachers. Finding poachers …

Learning optimal prescriptive trees from observational data

N Jo, S Aghaei, A Gómez, P Vayanos - arxiv preprint arxiv:2108.13628, 2021 - arxiv.org
We consider the problem of learning an optimal prescriptive tree (ie, an interpretable
treatment assignment policy in the form of a binary tree) of moderate depth, from …

Are drivers ready for traffic enforcement drones?

A Rosenfeld - Accident Analysis & Prevention, 2019 - Elsevier
Traffic enforcement drones reduce high-risk driving behavior which often leads to traffic
crashes. However, the introduction of drones may face a public acceptance challenge which …

When crowdsourcing meets unmanned vehicles: Toward cost-effective collaborative urban sensing via deep reinforcement learning

L Ding, D Zhao, M Cao, H Ma - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
Mobile crowdsensing (MCS) and unmanned vehicle sensing (UVS) provide two
complementary paradigms for large-scale urban sensing. Generally, MCS has a lower cost …

To signal or not to signal: Exploiting uncertain real-time information in signaling games for security and sustainability

E Bondi, H Oh, H Xu, F Fang, B Dilkina… - Proceedings of the AAAI …, 2020 - ojs.aaai.org
Motivated by real-world deployment of drones for conservation, this paper advances the
state-of-the-art in security games with signaling. The well-known defender-attacker security …

[HTML][HTML] Optimal cruiser-drone traffic enforcement under energy limitation

A Rosenfeld, O Maksimov - Artificial Intelligence, 2019 - Elsevier
Drones can assist in mitigating traffic accidents by deterring reckless drivers, leveraging their
flexible mobility. In the real-world, drones are fundamentally limited by their battery/fuel …

Reinforcement learning for unified allocation and patrolling in signaling games with uncertainty

A Venugopal, E Bondi, H Kamarthi, K Dholakia… - arxiv preprint arxiv …, 2020 - arxiv.org
Green Security Games (GSGs) have been successfully used in the protection of valuable
resources such as fisheries, forests and wildlife. While real-world deployment involves both …

When can the defender effectively deceive attackers in security games?

T Nguyen, H Xu - Proceedings of the AAAI Conference on Artificial …, 2022 - ojs.aaai.org
This paper studies defender patrol deception in general Stackelberg security games (SSGs),
where a defender attempts to alter the attacker's perception of the defender's patrolling …

Regstar: efficient strategy synthesis for adversarial patrolling games

D Klaška, A Kučera, V Musil… - Uncertainty in Artificial …, 2021 - proceedings.mlr.press
We design a new efficient strategy synthesis method applicable to adversarial patrolling
problems on graphs with arbitrary-length edges and possibly imperfect intrusion detection …