Reinforcement Learning for Learning Rate Control
CoRR, 2017 7 pages, 9 ...
Chang Xu 0008 +3 more
openaire +2 more sources
The Emergence of Special Skill in Basketball Free Throw with Different Levels of Expertise [PDF]
رشد و یادگیری حرکتی ورزشی, 2019 The aim of this study was to investigate the emergence of special skill in basketball free throw at different skill levels based on Newell's model of learning stages.
Faranak Poorhosseini +2 more
doaj +1 more source
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
Iterative learning control of integer and noninteger order: An overview [PDF]
Scientific Technical Review, 2014 This paper provides an overview of the recently presented and published results relating to the use of iterative learning control (ILC) based on and integer and fractional order.
Lazarević Mihailo
doaj
Norm Optimal Iterative Learning Control with Application to Problems in Accelerator based Free Electron Lasers and Rehabilitation Robotics [PDF]
, 2010 This paper gives an overview of the theoretical basis of the norm optimal approach to iterative learning control followed by results that describe more recent work which has experimentally benchmarking the performance that can be achieved.
Schmidt, C +27 more
core +1 more source
Some new results on iterative learning control of noninteger order [PDF]
Scientific Technical Review, 2014 Iterative learning control (ILC) is one of the recent topics in control theories and it is a powerful control concept that iteratively improves the behavior of processes repetitive in their nature.
Lazarević Mihailo
doaj
Multilayer perceptron learning control [PDF]
, 1996 It has been shown that, when used for pattern recognition with supervised learning, a network with one hidden layer tends to the optimal Bayesian classifier provided that three parameters simultaneously tend to certain limiting values: the sample size and the number of cells in the hidden layer must both tend to infinity and some mean error function ...
Verley, Gilles +1 more
openaire +2 more sources
Effects of working memory load and CS-US intervals on delay eyeblink conditioning
npj Science of Learning, 2023 Eyeblink conditioning is used in many species to study motor learning and make inferences about cerebellar function. However, the discrepancies in performance between humans and other species combined with evidence that volition and awareness can ...
Leila Etemadi +2 more
doaj +1 more source
Deep Controlled Learning for Inventory Control
European Journal of Operational ResearchThe application of Deep Reinforcement Learning (DRL) to inventory management is an emerging field. However, traditional DRL algorithms, originally developed for diverse domains such as game-playing and robotics, may not be well-suited for the specific challenges posed by inventory management.
Tarkan Temizöz +4 more
openaire +4 more sources