27 citations · 206 across the 63 of their papers we have counts for
11 papers · 1 filter
Optimal Control of Material Micro-Structures
Aayushman Sharma, Zirui Mao, Haiying Yang +3
In this paper, we consider the optimal control of material micro-structures. Such material micro-structures are modeled by the so-called phase field model. We study the underlying…
Enhanced Meta Reinforcement Learning using Demonstrations in Sparse Reward Environments
Desik Rengarajan, Sapana Chaudhary, Jaewon Kim +2
Meta reinforcement learning (Meta-RL) is an approach wherein the experience gained from solving a variety of tasks is distilled into a meta-policy. The meta-policy, when adapted ov…
Robust Reinforcement Learning Algorithm for Vision-based Ship Landing of UAVs
Vishnu Saj, Bochan Lee, Dileep Kalathil +1
This paper addresses the problem of developing an algorithm for autonomous ship landing of vertical take-off and landing (VTOL) capable unmanned aerial vehicles (UAVs), using only…
DETERRENT: Detecting Trojans using Reinforcement Learning
Vasudev Gohil, Satwik Patnaik, Hao Guo +3
Insertion of hardware Trojans (HTs) in integrated circuits is a pernicious threat. Since HTs are activated under rare trigger conditions, detecting them using random logic simulati…
Meta-Learning Online Control for Linear Dynamical Systems
Deepan Muthirayan, Dileep Kalathil, Pramod P. Khargonekar
In this paper, we consider the problem of finding a meta-learning online control algorithm that can learn across the tasks when faced with a sequence of (similar) control tasks…
Robust Reinforcement Learning using Offline Data
Kishan Panaganti, Zaiyan Xu, Dileep Kalathil +1
The goal of robust reinforcement learning (RL) is to learn a policy that is robust against the uncertainty in model parameters. Parameter uncertainty commonly occurs in many real-w…
Distributed Learning of Neural Lyapunov Functions for Large-Scale Networked Dissipative Systems
Amit Jena, Tong Huang, S. Sivaranjani +2
This paper considers the problem of characterizing the stability region of a large-scale networked system comprised of dissipative nonlinear subsystems, in a distributed and comput…
Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning
Ruida Zhou, Tao Liu, Dileep Kalathil +2
We study policy optimization for Markov decision processes (MDPs) with multiple reward value functions, which are to be jointly optimized according to given criteria such as propor…
The Impact of Heavy-Duty Vehicle Electrification on Large Power Grids: a Synthetic Texas Case Study
Rayan El Helou, S. Sivaranjani, Dileep Kalathil +2
The electrification of heavy-duty vehicles (HDEVs) is a nascent and rapidly emerging avenue for decarbonization of the transportation sector. In this paper, we examine the impacts…
Reinforcement Learning with Sparse Rewards using Guidance from Offline Demonstration
Desik Rengarajan, Gargi Vaidya, Akshay Sarvesh +2
A major challenge in real-world reinforcement learning (RL) is the sparsity of reward feedback. Often, what is available is an intuitive but sparse reward function that only indica…
Intelligent Vision-based Autonomous Ship Landing of VTOL UAVs
Bochan Lee, Vishnu Saj, Moble Benedict +1
The paper discusses an intelligent vision-based control solution for autonomous tracking and landing of Vertical Take-Off and Landing (VTOL) capable Unmanned Aerial Vehicles (UAVs)…