Zobrazeno 1 - 10
of 541
pro vyhledávání: '"Gatsis A"'
The goal of Bayesian inverse reinforcement learning (IRL) is recovering a posterior distribution over reward functions using a set of demonstrations from an expert optimizing for a reward unknown to the learner. The resulting posterior over rewards c
Externí odkaz:
http://arxiv.org/abs/2407.10971
Decision making and learning in the presence of uncertainty has attracted significant attention in view of the increasing need to achieve robust and reliable operations. In the case where uncertainty stems from the presence of adversarial attacks thi
Externí odkaz:
http://arxiv.org/abs/2403.15207
Reinforcement learning (RL) excels in applications such as video games, but ensuring safety as well as the ability to achieve the specified goals remains challenging when using RL for real-world problems, such as human-aligned tasks where human safet
Externí odkaz:
http://arxiv.org/abs/2401.13148
Neural networks (NNs) have been shown to learn complex control laws successfully, often with performance advantages or decreased computational cost compared to alternative methods. Neural network controllers (NNCs) are, however, highly sensitive to d
Externí odkaz:
http://arxiv.org/abs/2309.03846
In this paper, we evaluate the different fully homomorphic encryption schemes, propose an implementation, and numerically analyze the applicability of gradient descent algorithms to solve quadratic programming in a homomorphic encryption setup. The l
Externí odkaz:
http://arxiv.org/abs/2309.01559
Reinforcement learning (RL) has demonstrated impressive performance in various areas such as video games and robotics. However, ensuring safety and stability, which are two critical properties from a control perspective, remains a significant challen
Externí odkaz:
http://arxiv.org/abs/2304.04066
Autor:
Miao, Keyan, Gatsis, Konstantinos
Relying on recent research results on Neural ODEs, this paper presents a methodology for the design of state observers for nonlinear systems based on Neural ODEs, learning Luenberger-like observers and their nonlinear extension (Kazantzis-Kravaris-Lu
Externí odkaz:
http://arxiv.org/abs/2212.00866
Autor:
Ayyagari, Krishna Sandeep, Abraham, Sherin Ann, Yao, Yiyun, Ghosh, Shibani, Flores-Espino, Francisco, Nagarajan, Adarsh, Gatsis, Nikolaos
The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated
Externí odkaz:
http://arxiv.org/abs/2210.08550
Phasor measurement units ({PMUs}) have become instrumental in modern power systems for enabling real-time, wide-area monitoring and control. Accordingly, many studies have investigated efficient and robust dynamic state estimation (DSE) methods in or
Externí odkaz:
http://arxiv.org/abs/2202.13254
Modern control systems routinely employ wireless networks to exchange information between spatially distributed plants, actuators and sensors. With wireless networks defined by random, rapidly changing transmission conditions that challenge assumptio
Externí odkaz:
http://arxiv.org/abs/2201.09859