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Now showing items 11-16 of 16
LEARNING ROBOT MANIPULATION TASKS VIA OBSERVATION
(2019-12-06)
The coexistence of humans and robots has been the aspiration of many scientific endeavors in the past century. Most anthropomorphic or industrial robots are highly articulated and complex machines, which are designed to ...
MULTI-PLAYER H1 DIFFERENTIAL GAME USING ON-POLICY AND OFF-POLICY REINFORCEMENT LEARNING
(2021-08-03)
This work studies a multi-player H-infinity differential game for systems of general linear dynamics. In this game, multiple players design their control inputs to minimize their cost functions in the presence of worst-case ...
Neural Network Architecture Optimization Using Reinforcement Learning
(2023-05-19)
Deep learning has emerged as an increasingly valuable tool, employed across a myriad of applications. However, the intricacies of deep learning systems, stemming from their sensitivity to specific network architectures, ...
ADAPTIVE OPTIMAL TRACKING OF UNCERTAIN DISCRETE-TIME SYSTEMS
(2017-08-01)
Optimal feedback control design has been responsible for much of the successful performance of engineered systems in aerospace, manufacturing, industrial processes, vehicles, ships, robotics, and elsewhere. Although most ...
On-Line Environment Adaptation for User Performance Optimization
(2023-08-14)
In today’s fast-paced and globally connected world, businesses are creating products with more significance to user personalization and customization. This has amplified the importance of capturing and learning user ...
Learning and control for complex multiagent systems
(2023-12-06)
**Please note that the full text is embargoed until 02/01/2025** Complex multiagent systems (MASs) are pervasive in various fields, from power system networks, and autonomous robotics to traffic management, where groups ...