226 citations · 729 across the 62 of their papers we have counts for
9 papers · 1 filter
Deep Reinforcement Learning for Adaptive Traffic Signal Control
Kai Liang Tan, Subhadipto Poddar, Anuj Sharma +1
Many existing traffic signal controllers are either simple adaptive controllers based on sensors placed around traffic intersections, or optimized by traffic engineers on a fixed s…
A perspective on multi-agent communication for information fusion
Homagni Saha, Vijay Venkataraman, Alberto Speranzon +1
Collaborative decision making in multi-agent systems typically requires a predefined communication protocol among agents. Usually, agent-level observations are locally processed an…
On Higher-order Moments in Adam
Zhanhong Jiang, Aditya Balu, Sin Yong Tan +3
In this paper, we investigate the popular deep learning optimization routine, Adam, from the perspective of statistical moments. While Adam is an adaptive lower-order moment based…
A Fast Saddle-Point Dynamical System Approach to Robust Deep Learning
Yasaman Esfandiari, Aditya Balu, Keivan Ebrahimi +3
Recent focus on robustness to adversarial attacks for deep neural networks produced a large variety of algorithms for training robust models. Most of the effective algorithms invol…
Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents
Xian Yeow Lee, Sambit Ghadai, Kai Liang Tan +2
Robustness of Deep Reinforcement Learning (DRL) algorithms towards adversarial attacks in real world applications such as those deployed in cyber-physical systems (CPS) are of incr…
Learning to Cope with Adversarial Attacks
Xian Yeow Lee, Aaron Havens, Girish Chowdhary +1
The security of Deep Reinforcement Learning (Deep RL) algorithms deployed in real life applications are of a primary concern. In particular, the robustness of RL agents in cyber-ph…