Decision-Time Learning and Planning Integrated Control for the Mild Hyperbaric Chamber by Nan Zhang, Qijing Lin, Zhuangde Jiang

“…Furthermore, a decision-time planning algorithm is developed and the planning process is further guided by incorporating a value network and an enhanced online policy. …”
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From humans to algorithms: A sociotechnical framework of workplace surveillance by Oliver G. Kayas, Chin Eang Ong, H.M. Belal

“…Current frameworks also underplay the influence of digital technology and fail to account for the impact modern digital technologies, such as artificial intelligence algorithms, have on shaping the characteristics of surveillance. …”
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RS-DRL-based offloading policy and UAV trajectory design in F-MEC systems by Yulu Yang, Han Xu, Zhu Jin, Tiecheng Song, Jing Hu, Xiaoqin Song

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Trust Region Policy Learning for Adaptive Drug Infusion with Communication Networks in Hypertensive Patients by Mai The Vu, Seong Han Kim, Ha Le Nhu Ngoc Thanh, Majid Roohi, Tuan Hai Nguyen

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Reverse Engineering Segment Routing Policies and Link Costs With Inverse Reinforcement Learning and EM by Kai Wang, Chee Wei Tan

“…This study delves into the inverse problem of a general type of SR and attempts to infer the SR policies given expert traffic traces. To this end, we propose MoME, a Mixture-of-Experts (MoE) model using the Maximum Entropy Inverse Reinforcement Learning (MaxEnt-IRL) framework that is capable of incorporating diverse features (e.g., router, link and context) and capturing complex relationships in the link cost, in combination with an Expectation-Maximization (EM) based iterative algorithm that jointly infers link costs and SR policy classes. …”
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Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…The proposed method is based on the proximal policy optimization (PPO) algorithm of the Actor-Critic framework, and defect detection is achieved by performing a series of scaling and translation operations on the mask. …”
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Decentralized Voltage and Var Control of Active Distribution Network Based on Parameter-Sharing Deep Reinforcement Learning by Binqiao Zhang, Changlin He

“…By allowing agents to share parts of their neural network, the proposed Parameter Sharing - twin-delay deep deterministic policy gradient algorithm improves the stability and efficiency of voltage regulation. …”
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Optimising entanglement distribution policies under classical communication constraints assisted by reinforcement learning by Jan Li, Tim Coopmans, Patrick Emonts, Kenneth Goodenough, Jordi Tura, Evert van Nieuwenburg

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Clustering Analysis of the Energy Mix in Romania Using K-Means Algorithm by Cristina (Antohi) Barbu, Stefan-Mihai Petrea, Corina Sbughea, Cristina Gabriela Zamfir

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An Exploratory Application of Machine Learning Algorithms in Estimating Net Salaries in Romania by Adriana Aiftincăi

“…The paper contributes to the integration and use of artificial intelligence methods in macroeconomic forecasting and labor market analysis. …”
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Economic Development of the Latin American Integration Association: Trends and Prospects by M. N. Tolmachev, E. V. Nikiforova, A. P. Tsypin

“…The testing of the author’s methodology aimed at studying the economic development of LAIA member countries allows us to argue about the operability of the algorithm, which made it possible to establish the low efficiency of the integration policy of Latin American countries, which, despite the significant level of national wealth, does not allow us to form a trend towards economic growth, a decrease in dependence on the export of natural capital, and an increase in the standard of living of the population. …”
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A Reinforcement Learning Approach to Personalized Asthma Exacerbation Prediction Using Proximal Policy Optimization by Dahiru Adamu Aliyu, Emelia Akashah Patah Akhir, Maryam Omar Abdullah Sawad, Jameel Shehu Yalli, Yahaya Saidu

“…The model achieved 96.60% accuracy, 95.79% precision, 96.65% recall, and 95.92% F1-score, outperforming baseline RL algorithms such as Deep Q-Learning (92.21% accuracy), Advantage Actor-Critic (94.34% accuracy), and Trust Region Policy Optimization (95.12% accuracy). …”
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Heterogeneous Multi-Agent Task Planning Method in Complex Marine Environment by Shoumin Wang, Ning Niu, Zhichao Wang, Yaxuan Lv, Jing Zhang

“…The task allocation framework combines the proximal policy optimization algorithm with experience replay to train an Actor network, ensuring stable iterative updates of task allocation policies toward high-reward directions. …”
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Adaptive RFID Data Scheduling Using Proximal Policy Optimization for Reducing Data Processing Latency by Guowei Guo, Xinsen Yang, Ziwei Liang, Zeli Xi, Ximei Zhan, Peisong Li

“…This paper presents a novel approach for dynamically offloading data using deep reinforcement learning, specifically employing the Proximal Policy Optimization (PPO) algorithm. The proposed method utilizes a central controller equipped with the PPO model to make intelligent, real-time reader selection decisions based on environmental factors such as reader load, tag mobility, and network conditions. …”
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Research on the policy inconsistency, network motifs and low carbon effects for municipal solid waste management by Bo Lv, Tianxu Cui, Daiheng Li, Weiyue Yao

“…This study combines the policy consistency formula, a four-node network motif evolution algorithm, and the Exponential Random Graph Model (ERGM), analyzing MSWM green network motifs with carbon emission data. …”
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Explainable post hoc portfolio management financial policy of a Deep Reinforcement Learning agent. by Alejandra de-la-Rica-Escudero, Eduardo C Garrido-Merchán, María Coronado-Vaca

“…In this work, driven by the motivation of making DRL explainable, we developed a novel Explainable DRL (XDRL) approach for PM, integrating the Proximal Policy Optimization (PPO) DRL algorithm with the model agnostic explainable machine learning techniques of feature importance, SHAP and LIME to enhance transparency in prediction time. …”
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RETRACTED: Utilizing Generative Design Algorithms for Innovative Structural Engineering Solutions by Ramesh B, RJ Anandhi, Singla Atul, Chandra Pradeep Kumar, Sethi Vandana Arora, Abood Ahmed Salam

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Investigating the hydrogen renaissance in the global energy transition with AI integration by Abderrahim Lakhouit

“…In storage, AI-driven algorithms are improving the management of hydrogen in large-scale storage systems, helping to mitigate issues such as leakage and optimizing storage conditions. …”
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Prospects of integrative and hybrid approaches to assessing undeclared work by Cymbal О. І., Ostafiichuk Ya. V.

“…The article considers the prospects for the formation of a new methodology for researching undeclared work in order to develop an evidence-based policy on to minimize it. In the context of European integration, Ukraine has an obligation to join European initiatives to combat undeclared work and make this activity a systemic component of the relevant state policy. …”
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Federated Reinforcement Learning in Stock Trading Execution: The FPPO Algorithm for Information Security by Haogang Feng, Yue Wang, Shida Zhong, Tao Yuan, Zhi Quan

“…This paper presents the Federated Proximal Policy Optimization (FPPO) algorithm, an adaptive trade execution framework that leverages joint reinforcement learning. …”
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