Results 81 to 90 of about 35,395 (320)

POMA-C: A Framework for Solving the Problem of Precise Anesthesia Control Under Incomplete Observation Environment in Low-Income Areas

IEEE Access
This paper introduces the POMA-C (Partial Observable Model for Anesthesia Control) framework, developed to address the challenge of anesthesia management in environments with incomplete physiological monitoring, such as low-resource settings where ...
Yide Yu, Huijie Li, Dennis Wong, Anmin Hu, Jian Huo, Yan Ma, Yue Liu   +6 more
doaj   +1 more source

Deciding the Value 1 Problem for #-acyclic Partially Observable Markov Decision Processes

, 2012
The value 1 problem is a natural decision problem in algorithmic game theory. For partially observable Markov decision processes with reachability objective, this problem is defined as follows: are there strategies that achieve the reachability objective
Gimbert, Hugo, Oualhadj, Youssouf
core   +1 more source

Experimental results : Reinforcement Learning of POMDPs using Spectral Methods [PDF]

, 2017
We propose a new reinforcement learning algorithm for partially observable Markov decision processes (POMDP) based on spectral decomposition methods.
Anandkumar, Animashree, Azizzadenesheli, Kamyar, Lazaric, Alessandro   +2 more
core   +1 more source

A primer on partially observable Markov decision processes (POMDPs) [PDF]

, 2021
Iadine Chadès, Luz Valerie Pascal, Sam Nicol, Cameron S. Fletcher, Jonathan Ferrer‐Mestres   +4 more
openalex   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

A UAV Path Planning Method Based on Deep Reinforcement Learning With Dense Rewards

IEEE Open Journal of Vehicular Technology
Most state-of-the-art (SOTA) uncrewed aerial vehicle (UAV) path planning approaches depend on global environmental knowledge. While algorithms like adaptive soft actor-critic (ASAC) have improved training efficiency, their obstacle avoidance in partially
Jianhong Zhou, Yong Wang, Qian Xie, Zixia Shang, Yinliang Jiang, Qiuyu DU   +5 more
doaj   +1 more source

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

A Method for Speeding Up Value Iteration in Partially Observable Markov\n Decision Processes [PDF]

, 2013
Nevin L. Zhang, Stephen S. Lee, Weihong Zhang   +2 more
openalex   +2 more sources

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai, Yefeng Yang, Tao Huang, Boyang Li   +3 more
wiley   +1 more source

Trajectory Aware Deep Reinforcement Learning Navigation Using Multichannel Cost Maps

Robotics
Deep reinforcement learning (DRL)-based navigation in an environment with dynamic obstacles is a challenging task due to the partially observable nature of the problem.
Tareq A. Fahmy, Omar M. Shehata, Shady A. Maged   +2 more
doaj   +1 more source