A dual-method approach integrating dynamic QCA and LightGBM-SHAP algorithms to uncover the configuration paths and key drivers of water resource green efficiency in China by Naiming He, Rijia Ding

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Impact of integrating type-1 distributed generation on distribution network using modified genetic algorithm and voltage stability index: a technical and cost–benefit analysis appr... by Olakunle Elijah Olabode, Daniel Oluwaseun Akinyele, Titus Oluwasuji Ajewole, Samuel Okeolu Omogoye, Akeem Abimbola Raji

“…The paper proposed a relevant policy framework on DG integration, which filled knowledge gap in the previous studies. …”
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Developing and integrating a destination decision support algorithm into an innovative electronic communication platform to improve injury care service coordination in Rwanda: the... by Antonio Belli, Justine Davies, Lucia D'Ambruoso, Jean Marie Uwitonze, Sudha Jayaraman, Abebe Bekele, Agnieszka Ignatowicz, Aurore Nishimwe, Jean Claude Byiringiro, Laura Quinn, Barnabas Tobi Alayande, Jean Nepomuscene Sindikubwabo, Didier Hagumimana, Fabien Hagenimana, Gilbert Rukundo, Ephrem Daniel Sheferaw, Oda Munyura, Rob Rickard, Philbert Muhire, Irene Bagahirwa, Jeanne d’Arc Nyinawankusi, Collins Inkotanyi, Assuman Nuhu

“…This study describes the protocol to develop, roll-out and evaluate the effectiveness of a destination decision support algorithm (DDSA) integrated in an electronic communication platform, ‘912Rwanda’. …”
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Low-altitude Secure Communication Driven by Deep Reinforcement Learning: An Integrated Sensing and Communication Design by Zhiqiang WEI, Jiashuo ZHANG, Fan LIU, Zai YANG, Zesong FEI

“…Using the Deep Deterministic Policy Gradient (DDPG) algorithm, the optimal framework is learned over time, dynamically optimizing the communication UAV’s trajectory and resource allocation to maximize long-term sensing and secure communication performance. …”
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Robust Adaptive Fractional-Order PID Controller Design for High-Power DC-DC Dual Active Bridge Converter Enhanced Using Multi-Agent Deep Deterministic Policy Gradient Algorithm for... by Seyyed Morteza Ghamari, Daryoush Habibi, Asma Aziz

“…To achieve this adaptability, a Multi-Agent Reinforcement Learning (MARL) approach is adopted, where each gain of the controller is tuned individually using the Deep Deterministic Policy Gradient (DDPG) algorithm. This structure enhances the controller’s ability to respond to external disturbances with greater robustness and adaptability. …”
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A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy by Hua Zhan, Changxu Jiang, Zhen Lin

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AI-driven disinformation: policy recommendations for democratic resilience by Alexander Romanishyn, Olena Malytska, Vitaliy Goncharuk

“…The increasing integration of artificial intelligence (AI) into digital communication platforms has significantly transformed the landscape of information dissemination. …”
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MACRPO: Multi-agent cooperative recurrent policy optimization by Eshagh Kargar, Ville Kyrki

“…We focus on improving information sharing between agents and propose a new multi-agent actor-critic method called Multi-Agent Cooperative Recurrent Proximal Policy Optimization (MACRPO). We propose two novel ways of integrating information across agents and time in MACRPO: First, we use a recurrent layer in the critic’s network architecture and propose a new framework to use the proposed meta-trajectory to train the recurrent layer. …”
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Artificial intelligence-based forecasting models for integrated energy system management planning: An exploration of the prospects for South Africa by Senthil Krishnamurthy, Oludamilare Bode Adewuyi, Emmanuel Luwaca, Mukovhe Ratshitanga, Prathaban Moodley

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Dengue Contingency Planning: From Research to Policy and Practice. by Silvia Runge-Ranzinger, Axel Kroeger, Piero Olliaro, Philip J McCall, Gustavo Sánchez Tejeda, Linda S Lloyd, Lokman Hakim, Leigh R Bowman, Olaf Horstick, Giovanini Coelho

“…Countries tend to rely on intensified vector control as their outbreak response, with minimal focus on integrated management of clinical care, epidemiological, laboratory and vector surveillance, and risk communication. …”
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A Deep Reinforcement Learning Framework for Last-Mile Delivery with Public Transport and Traffic-Aware Integration: A Case Study in Casablanca by Amine Mohamed El Amrani, Mouhsene Fri, Othmane Benmoussa, Naoufal Rouky

“…The pickup and delivery operations are optimized with the proximal policy optimization algorithm within this environment, and experiments are conducted to assess the effectiveness of public transportation integration and three different exploration strategies. …”
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PolicySegNet: a policy-based reinforcement learning framework with pretrained embeddings and transformer decoder for joint brain tumors segmentation and classification in MRI by Vishv Patel, Vandana Patel, Aakash Shinde

“…Unlike typical fine-tuning approaches, the SegFormer encoder remains frozen, enabling efficient training on limited domain-specific data. PolicySegNet uniquely integrates a policy-based reinforcement learning algorithm—specifically proximal policy optimization (PPO)—to jointly optimize the decoder and classifier based on a reward signal that balances segmentation accuracy with classification performance. …”
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Novel concept for the healthy population influencing factors by Yuhao Shen, Jichao Wang, Lihua Ma, Huizhe Yan

“…The insights generated by these models will help develop health policies and intervention policies to improve the health status of mobile populations, narrow disparities, and promote social and economic stability. …”
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Learning-Based Variable Admittance Control Combined with NMPC for Contact Force Tracking in Unknown Environments by Yikun Zhang, Jianjun Yao, Chen Qian

“…Based on this analysis, a variable admittance control strategy is proposed using the deep deterministic policy gradient algorithm, enabling the online tuning of admittance parameters through reinforcement learning. …”
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Optimizing Energy Consumption and Latency in IoT Through Edge Computing in Air–Ground Integrated Network With Deep Reinforcement Learning by Vitou That, Kimchheang Chhea, Jung-Ryun Lee

“…The performance of the proposed algorithm is compared to traditional algorithms, including the Whale Optimization Algorithm (WOA), Gradient Search with Barrier, and Bayesian Optimization (BO). …”
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Research and practice on self-organization architecture of smart pipe in mobile internet by Fei XUE, Yuhui XU, Liang ZHANG, Ying LI

“…According to the 3GPP specification,a new self-organization network of smart pipe in mobile internet was addressed.By introducing integrated policy control function,the external signals were supervised periodically,and the best optimized network strategies were predicted by the recurrent neural network algorithm,delivered by PCRF,and updated automatically with feedback of the regulations.This solution was effectively applied in scenarios such as speed limit of large traffic users,network protection under high load,and online advertisement recommendation etc.…”
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Crafting desirable climate trajectories with reinforcement learning explored socio-environmental simulations by James Rudd-Jones, Fiona Thendean, María Pérez-Ortiz

“…Modelling competition is key to increased realism in these simulations, as such we employ policy interpretation by visualizing what states lead to more uncertain behavior, to understand algorithm failure. …”
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Policy-Based Smart Contracts Management for IoT Privacy Preservation by Mohsen Rouached, Aymen Akremi, Mouna Macherki, Naoufel Kraiem

“…More specifically, we propose a new model that leverages the properties of private blockchain and smart contracts to ensure user data privacy when shared with others. We define policy-based algorithms and notations to assist users in managing smart contracts responsible for registering and controlling their IoT devices. …”
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Controlling Cable Driven Parallel Robots Operations—Deep Reinforcement Learning Approach by Muhammad Kamran Joyo, Abdulmajeed M. Alenezi, Wenfu Xu, Mohamad A. Alawad, Muhmmad Tayyab Yaqoob, Noor Maricar, Sheroz Khan

“…This article explores the complex challenges involved in implementing Deep Reinforcement Learning (DRL) algorithms on a cable-driven parallel robot. A key contribution of this work as specific advancement is the integration of a Proportional-Integral-Derivative (PID) controller within the RL framework, establishing a unique approach to CDPR control that leverages adaptive learning capabilities. …”
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Big Questions of Artificial Intelligence (AI) in Public Administration and Policy by Mehmet Metin Uzun, Mete Yıldız, Murat Önder

“…Integrating AI into public administration and the policy-making process allows numerous opportunities. …”
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