Results 51 to 60 of about 171,350 (313)

Uncertainty-aware Path Planning using Reinforcement Learning and Deep Learning Methods [PDF]

Computer and Knowledge Engineering, 2020
This paper proposes new algorithms to improve Reinforcement Learning (RL) and Deep Q-Network (DQN) methods for path planning considering uncertainty in the perception of environment.
Nematollah Ab azar, Aref Shahmansoorian, Mohsen Davoudi   +2 more
doaj   +1 more source

Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent [PDF]

Proceedings of the Twenty-Ninth International Joint Conference IJCAI20 (2020) 3051-3057, 2020
Existing convergence analyses of Q-learning mostly focus on the vanilla stochastic gradient descent (SGD) type of updates. Despite the Adaptive Moment Estimation (Adam) has been commonly used for practical Q-learning algorithms, there has not been any convergence guarantee provided for Q-learning with such type of updates.
arxiv   +1 more source

Online intelligent maneuvering penetration methods of missile with respect to unknown intercepting strategies based on reinforcement learning

Electronic Research Archive, 2022
This paper considers the maneuvering penetration methods of missile which do not know the intercepting strategies of the interceptor beforehand. Based on reinforcement learning, the online intelligent maneuvering penetration methods of missile are ...
Yaokun Wang, Kun Zhao , Juan L. G. Guirao , Kai Pan, Huatao Chen   +4 more
doaj   +1 more source

Sufficient Exploration for Convex Q-learning [PDF]

arXiv, 2022
In recent years there has been a collective research effort to find new formulations of reinforcement learning that are simultaneously more efficient and more amenable to analysis. This paper concerns one approach that builds on the linear programming (LP) formulation of optimal control of Manne.
arxiv  

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

Suppressing Overestimation in Q-Learning through Adversarial Behaviors [PDF]

arXiv, 2023
The goal of this paper is to propose a new Q-learning algorithm with a dummy adversarial player, which is called dummy adversarial Q-learning (DAQ), that can effectively regulate the overestimation bias in standard Q-learning. With the dummy player, the learning can be formulated as a two-player zero-sum game.
arxiv  

Cell‐free and extracellular vesicle microRNAs with clinical utility for solid tumors

Molecular Oncology, EarlyView.
Cell‐free microRNAs (cfmiRs) are small‐RNA circulating molecules detectable in almost all body biofluids. Innovative technologies have improved the application of cfmiRs to oncology, with a focus on clinical needs for different solid tumors, but with emphasis on diagnosis, prognosis, cancer recurrence, as well as treatment monitoring.
Yoshinori Hayashi, Janelle‐Cheri Millen, Romela Irene Ramos, Jennifer A. Linehan, Timothy G. Wilson, Dave S. B. Hoon, Matias A. Bustos   +6 more
wiley   +1 more source

Periodic Q-Learning

, 2020
The use of target networks is a common practice in deep reinforcement learning for stabilizing the training; however, theoretical understanding of this technique is still limited. In this paper, we study the so-called periodic Q-learning algorithm (PQ-learning for short), which resembles the technique used in deep Q-learning for solving infinite ...
Lee, Donghwan, He, Niao
openaire   +2 more sources

Integration of single‐cell and bulk RNA‐sequencing data reveals the prognostic potential of epithelial gene markers for prostate cancer

Molecular Oncology, EarlyView.
Prostate cancer is a leading malignancy with significant clinical heterogeneity in men. An 11‐gene signature derived from dysregulated epithelial cell markers effectively predicted biochemical recurrence‐free survival in patients who underwent radical surgery or radiotherapy.
Zhuofan Mou, Lorna W. Harries
wiley   +1 more source

Adaptive Q-learning

, 2013
Developing an effective multi-stage treatment strategy over time is one of the essential goals of modern medical research. Developing statistical inference, including constructing confidence intervals for parameters, is of key interest in studies applying dynamic treatment regimens.
Goldberg, Yair, Song, Rui, Kosorok, Michael R.   +2 more
openaire   +2 more sources