Y He, Y Liu, L Yang, X Qu - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
… on deepreinforcement learning (RL), we design an adaptive car-following trajectory control algorithm, which is called Deep Adaptive Control, to cope with different traffic risklevels… Deep …
Y Li - arXiv preprint arXiv:1701.07274, 2017 - arxiv.org
We give an overview of recent exciting achievements of deepreinforcement learning (RL). We discuss six core elements, six important mechanisms, and twelve applications. We start …
G Li, Y Yang, S Li, X Qu, N Lyu, SE Li - Transportation research part C …, 2022 - Elsevier
… risklevels … deepreinforcement learning algorithms combining with risk assessment functions are innovatively proposed to find an optimal driving strategy with the minimum expected risk…
… This risk-seeking value can be seen as a utility for the agent under a certain risk profile where c specifies the level of risk. For \(c>0\), the agent is risk-seeking and values risky states …
GA Anwar, X Zhang - Reliability Engineering & System Safety, 2024 - Elsevier
… risk optimization framework is proposed herein for building structures by developing a deep reinforcement … and (2) a deepreinforcement learning-enabled risk optimization model for …
F Li, Z Xu, D Cheng, X Wang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
… This is an NP-hard problem that is crucial for risk management in many real-world … -distance risk contagion process. To this end, we propose a novel risk-adaptive deepreinforcement …
… collision risk. The COLREGs are in place to reduce collision risk and indirectly affect the risk level by … between the rules and the risklevel, employing a measure of risk as a proxy for the …
E Benhamou, D Saltiel, JJ Ohana… - 2020 25th International …, 2021 - ieeexplore.ieee.org
… progress of deepreinforcement learning methods that have reached super human levels in … are highly sensitive to economic surprise and risk aversion level. Again to ensure somehow …
A Millea, A Edalat - International Journal of Financial Studies, 2022 - mdpi.com
… At the highest level a DeepReinforcement Learning (DRL) agent selects among a number … low-level agents. For the low-level agents, we use a set of Hierarchical Risk Parity (HRP) and …