Results 21 to 30 of about 16,805,949 (306)
Robust Tracking Control of Aerial Robots Via a Simple Learning Strategy-Based Feedback Linearization
IEEE Access, 2020 To facilitate accurate tracking in unknown/uncertain environments, this paper proposes a simple learning (SL) strategy for feedback linearization control (FLC) of aerial robots subject to uncertainties.
Mohit Mehndiratta +3 more
doaj +1 more source
CT-DQN: Control-Tutored Deep Reinforcement Learning [PDF]
, 2023 One of the major challenges in Deep Reinforcement Learning for control is the need for extensive training to learn a policy. Motivated by this, we present the design of the Control-Tutored Deep QNetworks (CT-DQN) algorithm, a Deep Reinforcement Learning ...
Francesco De Lellis +4 more
core
Metacognitive Control and Optimal Learning [PDF]
Cognitive Science, 2006 Abstract The notion of optimality is often invoked informally in the literature on metacognitive control. We provide a precise formulation of the optimization problem and show that optimal time allocation strategies depend critically on certain characteristics of the learning environment, such as the extent of time pressure, and the ...
Lisa K. Son, Rajiv Sethi
openaire +4 more sources
A Survey of Robotics Control Based on Learning-Inspired Spiking Neural Networks
Frontiers in Neurorobotics, 2018 Biological intelligence processes information using impulses or spikes, which makes those living creatures able to perceive and act in the real world exceptionally well and outperform state-of-the-art robots in almost every aspect of life. To make up the
Zhenshan Bing +4 more
doaj +1 more source
IEEE Access, 2021 COVID-19 has not affected all countries equally: developing countries have been more disadvantaged by the pandemic. Regarding global development, the COVID-19 pandemic has forced a step back in the path to attaining the Sustainable Development Goals ...
Ascension Lopez-Vargas +3 more
doaj +1 more source
Toward Multi-Agent Reinforcement Learning for Distributed Event-Triggered Control
, 2023 Event-triggered communication and control provide high control performance in networked control systems without overloading the communication network.
Baumann, Dominik, +2 more
core +2 more sources
rickstaa/stable-learning-control
A framework for training theoretically stable (and robust) Reinforcement Learning control ...
Rick Staa +3 more
core +3 more sources
Control-Tutored Reinforcement Learning: Towards the Integration of Data-Driven and Model-Based Control [PDF]
, 2022 We present an architecture where a feedback controller derived on an approximate model of the environment assists the learning process to enhance its data efficiency.
Francesco De Lellis +9 more
core
IEEE Access, 2022 Snake-like modular robots (MRs) are highly flexible, but, to traverse a challenging terrain or explore a region of interest, MR needs to attain efficient locomotion depending on a tradeoff between objectives like forward velocity and power consumption of
Akash Singh +3 more
doaj +1 more source
Scientific Reports, 2022 Postural sway and eye movements are potential biomarkers for dementia screening. Assessing the two movements comprehensively could improve the understanding of complicated syndrome for more accurate screening.
Yu Imaoka +3 more
doaj +1 more source