Results 41 to 50 of about 212,805 (267)

Ramp Metering Control Based on the Q-Learning Algorithm

Cybernetics and Information Technologies, 2015
Modern urban highways are under the influence of increased traffic demand and cannot fulfill the desired level of service anymore. In most of the cases there is no space available for any infrastructure building.
Ivanjko Edouard, Koltovska Nečoska Daniela, Gregurić Martin, Vujić Miroslav, Jurković Goran, Mandžuka Sadko   +5 more
doaj   +1 more source

Regularized Q-Learning

Advances in Neural Information Processing Systems 37
Q-learning is widely used algorithm in reinforcement learning community. Under the lookup table setting, its convergence is well established. However, its behavior is known to be unstable with the linear function approximation case. This paper develops a new Q-learning algorithm that converges when linear function approximation is used.
Han-Dong Lim, Donghwan Lee 0002
openaire   +3 more sources

Deep functional measurements of Fragile X syndrome human neurons reveal multiparametric electrophysiological disease phenotype

Communications Biology
Fragile X syndrome (FXS) is a neurodevelopmental disorder caused by hypermethylation of expanded CGG repeats (>200) in the FMR1 gene leading to gene silencing and loss of Fragile X Messenger Ribonucleoprotein (FMRP) expression. FMRP plays important roles
James J. Fink, Nathaniel Delaney-Busch, Ryan Dawes, Evanthia Nanou, Christopher Folts, Karthiayani Harikrishnan, Chris Hempel, Hansini Upadhyay, Trinh Nguyen, Himali Shroff, David Stoppel, Steven J. Ryan, Jane Jacques, Jennifer Grooms, Elizabeth Berry-Kravis, Mark F. Bear, Luis A. Williams, David Gerber, Mark Bunnage, Brinley Furey, Graham T. Dempsey   +20 more
doaj   +1 more source

Complexification through gradual involvement and reward Providing in deep reinforcement learning

Системный анализ и прикладная информатика
Training a relatively big neural network within the framework of deep reinforcement learning that has enough capacity for complex tasks is challenging. In real life the process of task solving requires system of knowledge, where more complex skills are ...
E. V. Rulko,
doaj   +1 more source

Q-learning [PDF]

Machine Learning, 1992
Q-learning (Watkins, 1989) is a simple way for agents to learn how to act optimally in controlled Markovian domains. It amounts to an incremental method for dynamic programming which imposes limited computational demands. It works by successively improving its evaluations of the quality of particular actions at particular states.
Watkins, C., Dayan, P.
openaire   +2 more sources

Smooth Q-learning: Accelerate Convergence of Q-learning Using Similarity

CoRR, 2021
An improvement of Q-learning is proposed in this paper. It is different from classic Q-learning in that the similarity between different states and actions is considered in the proposed method. During the training, a new updating mechanism is used, in which the Q value of the similar state-action pairs are updated synchronously. The proposed method can
Wei Liao, Xiaohui Wei, Jizhou Lai
openaire   +2 more sources

Modulation of Homer1 EVH1 domain internal dynamics by putative autism‐associated mutations

FEBS Letters, EarlyView.
The putative autism‐associated M65I and S97L variants of the EVH1 domain of the postsynaptic scaffold protein Homer1 do not exhibit substantial changes in their overall structure or partner binding. Both of them, but especially the M65I variant, show altered internal dynamics relative to the wild‐type domain on the μs‐ms timescale, indicated by the ...
Fanni Farkas, Brigitta Maruzs, Zsófia E. Kálmán, Tomas Klumpler, Gyula Batta, Bálint Péterfia, Zoltán Gáspári   +6 more
wiley   +1 more source

Offloading decision algorithm based on reinforcement learning for mobile edge computing

Dianzi Jishu Yingyong, 2021
For the problem of computing offloading decision in mobile edge computing, this paper proposes an offloading decision algorithm based on enhanced learning in multiuser MEC system.
Yang Ge, Zhang Heng
doaj   +1 more source

Identification of the plant mitochondrial OrfX protein: A mass spectrometry approach

FEBS Letters, EarlyView.
The mitochondrial genome of plants contains an open reading frame, orfx, which encodes a rare protein that has so far escaped mass spectrometric detection. The protein resembles the c‐subunit of bacterial twin‐arginine‐motif‐dependent protein translocases (TatC).
Matthias Döring, Jan de Jonge, Hans‐Peter Braun, Nils Rugen   +3 more
wiley   +1 more source

Developmental programmes drive cellular plasticity, disease progression and therapy resistance in lung adenocarcinoma

Molecular Oncology, EarlyView.
This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska, Stephany Gallardo, Nur S. Zainal, Leena Arora, Matthew Ellis, Maria‐Antoinette Lopez, Judith Austine, Sai Pittla, Serena J Chee, Aiman Alzetani, Emily C Shaw, Christian H Ottensmeier, Gareth J Thomas, Christopher J Hanley   +13 more
wiley   +1 more source