Results 71 to 80 of about 171,350 (313)

GAN Q-learning

, 2018
Distributional reinforcement learning (distributional RL) has seen empirical success in complex Markov Decision Processes (MDPs) in the setting of nonlinear function approximation. However, there are many different ways in which one can leverage the distributional approach to reinforcement learning.
Doan, Thang, Mazoure, Bogdan, Lyle, Clare   +2 more
openaire   +2 more sources

Q LEARNING REGRESSION NEURAL NETWORK [PDF]

Neural Network World, 2018
In this work, a Nadaraya-Watson kernel based learning system which owns general regression neural network topology is adapted to Q learning method to evaluate a quick and efficient action selection policy for reinforcement learning problems. By means of the proposed method Q value function is generalized and learning speed of Q agent is accelerated ...
Sangiil M., Ave M.
openaire   +2 more sources

Momentum Q-learning with Finite-Sample Convergence Guarantee [PDF]

arXiv, 2020
Existing studies indicate that momentum ideas in conventional optimization can be used to improve the performance of Q-learning algorithms. However, the finite-sample analysis for momentum-based Q-learning algorithms is only available for the tabular case without function approximations.
arxiv  

A Q-Learning Based Hybrid Meta-Heuristic for Integrated Scheduling of Disassembly and Reprocessing Processes Considering Product Structures and Stochasticity

Complex System Modeling and Simulation
Remanufacturing is regarded as a sustainable manufacturing paradigm of energy conservation and environment protection. To improve the efficiency of the remanufacturing process, this work investigates an integrated scheduling problem for disassembly and ...
Fuquan Wang, Yaping Fu, Kaizhou Gao, Yaoxin Wu, Song Gao   +4 more
doaj   +1 more source

Reinforcement learning with Gaussian process regression using variational free energy

Journal of Intelligent Systems, 2023
The essential part of existing reinforcement learning algorithms that use Gaussian process regression involves a complicated online Gaussian process regression algorithm.
Kameda Kiseki, Tanaka Fuyuhiko
doaj   +1 more source

Epigenome‐wide association study, meta‐analysis, and multiscore profiling of whole blood in Parkinson's disease

Annals of Clinical and Translational Neurology, EarlyView.
Abstract Objectives An increasing body of evidence indicates altered DNA methylation in Parkinson's disease, yet the reproducibility and utility of such methylation changes are largely unexplored. We aimed to further elucidate the role of dysregulated DNA methylation in Parkinson's disease and to evaluate the biomarker potential of methylation‐based ...
Ingeborg Haugesag Lie, Manuela M. X. Tan, Maren Stolp Andersen, Mathias Toft, Lasse Pihlstrøm   +4 more
wiley   +1 more source

Evidence of blood–brain barrier dysfunction and CSF immunoglobulin synthesis in Down Syndrome Regression Disorder

Annals of Clinical and Translational Neurology, EarlyView.
Abstract Objectives This study sought to evaluate proteomic, metabolomic, and immune signatures in the cerebrospinal fluid of individuals with Down Syndrome Regression Disorder (DSRD). Methods A prospective case–control study comparing proteomic, metabolomic, and immune profiles in individuals with DSRD was performed.
Jonathan D. Santoro, Neetha Paul Eduthan, Mellad M. Khoshnood, Saba Jafarpour, Natalie K. Boyd, Benjamin N. Vogel, Lina Nguyen, Lilia Kazerooni, Eleanor Britton, Hannah R. Lyford, Matthew D. Galbraith, Angela L. Rachubinski, Joaquin M. Espinosa   +12 more
wiley   +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

Expertness based cooperative Q-learning [PDF]

IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2002
By using other agents' experiences and knowledge, a learning agent may learn faster, make fewer mistakes, and create some rules for unseen situations. These benefits would be gained if the learning agent can extract proper rules from the other agents' knowledge for its own requirements.
Ahmadabadi, Majid Nili, Asadpour, Masoud
openaire   +3 more sources

Amygdala Neurodegeneration: A Key Driver of Visual Dysfunction in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Visual disability in Parkinson's disease (PD) is not fully explained by retinal neurodegeneration. We aimed to delineate the brain substrate of visual dysfunction in PD and its association with retinal thickness. Methods Forty‐two PD patients and 29 controls underwent 3‐Tesla MRI, retinal spectral‐domain optical coherence tomography,
Asier Erramuzpe, Ane Murueta‐Goyena, Antonio Jimenez‐Marin, Marian Acera, Sara Teijeira‐Portas, Rocío Del Pino, Tamara Fernández‐Valle, Ibai Diez, Unai Sainz‐Lugarezaresti, Naroa Ibarretxe‐Bilbao, Unai Ayala, Maitane Barrenechea, Alberto Cabrera‐Zubizarreta, Jesús Cortés, Juan Carlos Gómez‐Esteban, Iñigo Gabilondo   +15 more
wiley   +1 more source