Modeling cyber-physical human systems via an interplay between reinforcement learning and game theory
Predicting the outcomes of cyber-physical systems with multiple human interactions is a
challenging problem. This article reviews a game theoretical approach to address this issue …
challenging problem. This article reviews a game theoretical approach to address this issue …
Game theoretic modeling of driver and vehicle interactions for verification and validation of autonomous vehicle control systems
Autonomous driving has been the subject of incre-ased interest in recent years both in
industry and in academia. Serious efforts are being pursued to address legal, technical, and …
industry and in academia. Serious efforts are being pursued to address legal, technical, and …
Possible inspiration: drone-related literature and its potential for public perception research
S Komasová - Journal of Intelligent & Robotic Systems, 2021 - Springer
This article identifies the current leading streams in the research of drones across multiple
disciplines in order to identify topics and factors that have not been sufficiently considered in …
disciplines in order to identify topics and factors that have not been sufficiently considered in …
Game theoretic modeling of vehicle interactions at unsignalized intersections and application to autonomous vehicle control
In this paper, we discuss a game theoretic approach to model the time-extended, multi-step,
and interactive decision making of vehicles at unsignalized intersections. The vehicle …
and interactive decision making of vehicles at unsignalized intersections. The vehicle …
Control and optimization of batch processes
D Bonvin - Encyclopedia of Systems and Control, 2021 - Springer
A batch process is characterized by the repetition of time-varying operations of finite
duration. Due to the repetition, there are two independent “time” variables, namely, the run …
duration. Due to the repetition, there are two independent “time” variables, namely, the run …
Driver modeling through deep reinforcement learning and behavioral game theory
In this work, a synergistic combination of deep reinforcement learning and hierarchical game
theory is proposed as a modeling framework for behavioral predictions of drivers in highway …
theory is proposed as a modeling framework for behavioral predictions of drivers in highway …
Cooperative manipulators
F Caccavale - Encyclopedia of Systems and Control, 2021 - Springer
This chapter presents an overview of the main modeling and control issues related to
cooperative manipulation of a common object by means of two or more robotic manipulators …
cooperative manipulation of a common object by means of two or more robotic manipulators …
Autonomous and cooperative control of UAV cluster with multi-agent reinforcement learning
D Xu, G Chen - The Aeronautical Journal, 2022 - cambridge.org
In this paper, we expolore Multi-Agent Reinforcement Learning (MARL) methods for
unmanned aerial vehicle (UAV) cluster. Considering that the current UAV cluster is still in the …
unmanned aerial vehicle (UAV) cluster. Considering that the current UAV cluster is still in the …
Decision making in dynamic and interactive environments based on cognitive hierarchy theory, Bayesian inference, and predictive control
In this paper, we describe an integrated framework for autonomous decision making in a
dynamic and interactive environment. We model the interactions between the ego agent and …
dynamic and interactive environment. We model the interactions between the ego agent and …
Using machine learning algorithms to predict the risk of small Unmanned Aircraft System violations in the National Airspace System
D Truong, W Choi - Journal of Air Transport Management, 2020 - Elsevier
The increasing number of small Unmanned Aircraft System (sUAS) encounters with manned
aircraft or airports increases the risk of collision in the National Airspace System. The …
aircraft or airports increases the risk of collision in the National Airspace System. The …