Results 61 to 70 of about 6,304,901 (198)
Joint action loss for proximal policy optimization [PDF]
, 2023 PPO (Proximal Policy Optimization) is a state-of-the-art policy gradient algorithm that has been successfully applied to complex computer games such as Dota 2 and Honor of Kings.
Slabaugh, Greg +3 more
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Transfusion, EarlyView.Abstract Background Blood banks often use simple ordering rules that replenish stock to a target level when inventory falls below a trigger point. However, for products such as Low‐Titer group O Whole Blood (LTOWB), where utilization is intermittent, simple rules may not always be effective.
S. Safavi, John T. Blake
wiley +1 more source
Computer-Aided Quantum Algorithms for Real-Time Energy Market Trading
IEEE AccessThis study presents an innovative approach for optimizing real-time energy market trading strategies by integrating Proximal Policy Optimization (PPO) with Quantum Annealing (QA).
Jinghui Wu +4 more
doaj +1 more source
Shape Optimization of a Hydraulic Turbine Using Deep Reinforcement Learning
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 4, December 2026.ABSTRACT The present study explores the potential of deep reinforcement learning for the geometric optimization of a hydraulic turbine and compares its performance with that of an evolutionary algorithm. Shape optimization in fluid mechanics often leads to high‐dimensional, highly non‐linear problems, requiring efficient methods to approximate global ...
Simon Eyselein +3 more
wiley +1 more source
Mission‐Aligned Learning‐Informed Control of Autonomous Systems: Formulation and Foundations
Expert Systems, Volume 43, Issue 11, November 2026.ABSTRACT Research, innovation and practical capital investment have been increasing rapidly toward the realization of autonomous physical agents. This includes industrial and service robots, unmanned aerial vehicles, embedded control devices, and a number of other realizations of cybernetic/mechatronic implementations of intelligent autonomous devices.
Vyacheslav Kungurtsev +7 more
wiley +1 more source
Transductive Off-policy Proximal Policy Optimization [PDF]
Proximal Policy Optimization (PPO) is a popular model-free reinforcement learning algorithm, esteemed for its simplicity and efficacy. However, due to its inherent on-policy nature, its proficiency in harnessing data from disparate policies is ...
Xing, Junliang +4 more
core +1 more source
Optimization algorithm for immersive VR spatial interaction based on multimodal perceptual fusion
Discover Artificial IntelligenceTo solve the problem of “human-machine gap” caused by insufficient understanding of intentions in traditional Virtual Reality (VR) interaction, this study proposes a multimodal perception fusion interaction optimization algorithm called Sparse Attention ...
Hua He
doaj +1 more source
Proximal Policy Optimization in 5G, B5G, and 6G Communication Systems: A Systematic Review
Future InternetFifth-generation (5G), Beyond 5G (B5G), and sixth-generation (6G) wireless networks, along with the Internet of Things (IoT), are core communication infrastructure in smart cities.
Vijaya Kittu Manda +2 more
doaj +1 more source
Wavelength‐Multiplexed 2D Beam Steering via a Passive Diffractive Network
Advanced Optical Materials, Volume 14, Issue 37, 9 October 2026.Illustration of a wavelength‐multiplexed diffractive beam steering system, which is composed of K cascaded diffractive layers, each containing phase‐modulating elements that are jointly optimized using deep learning–based optimization. When illuminated with a set of wavelengths {λ1,λ2,…,λNw}$\{ {{{\lambda }_1},{{\lambda }_2},\ldots ,{{\lambda }_{{{N}_w}
Che‐Yung Shen +5 more
wiley +1 more source
Proximal policy optimization with model-based methods
, 2022 Model-free reinforcement learning methods have successfully been applied to practical applications such as decision-making problems in Atari games. However, these methods have inherent shortcomings, such as a high variance and low sample efficiency.
Zhang X(张鑫) +4 more
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