Artificial Intelligence and Politics: Legal Dilemmas and Risks to Democracy by Daniele Battista, Gabriele Uva

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A trajectory planning and tracking method based on deep hierarchical reinforcement learning by Jiajie Zhang, Bao-Lin Ye, Xin Wang, Lingxi Li, Bo Song

“…We design an upper-level decision model based on the trust region policy optimization algorithm integrated with long short-term memory to obtain more accurate strategies. …”
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Strategic Implementation of Super-Agents in Heterogeneous Multi-Agent Training for Advanced Military Simulation Adaptability by Huseyin Oktay Altun, Huseyin Furkan Ceran, Korkut Kutay Metin, Tolga Erol, Emre Fisne

“…Optimizing Heterogeneous Multi-Agent Training (HMAT) through scenario-specific adjustments to the Proximal Policy Optimization (PPO) algorithm, we tackle the complexity of tactical simulations. …”
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Adaptive Security Solutions for NOMA Networks: The Role of DDPG and RIS-Equipped UAVs by Syed Zain Ul Abideen, Abdul Wahid, Mian Muhammad Kamal

“…This method not only shows how flexible and successful the DDPG algorithm is at protecting wireless communications when used in conjunction with an RIS but it also highlights how much the algorithm has advanced secure communication systems.…”
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Geoecological Analysis of the Effects of Pipeline Transport on the Environment of Transit Regions (Voronezh Region, Russia) by L. A. Mezhova, A. M. Lugovskoy, Yu. N. Gladkiy, A. B. Glazyeva, O. Yu. Sushkova, L. B. Vampilova, A. A. Sokolova, L. A. Lugovskaya

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Reinforcement Learning and Multi-Access Edge Computing for 6G-Based Underwater Wireless Networks by Juan Carlos Cepeda-Pacheco, Mari Carmen Domingo

“…To address the NP-hard nature of this problem, we employ a deep reinforcement learning algorithm, Deep Deterministic Policy Gradient (DDPG), to solve it. …”
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Sustainable Innovation: Harnessing AI and Living Intelligence to Transform Higher Education by Hesham Mohamed Allam, Benjamin Gyamfi, Ban AlOmar

“…Addressing these issues requires clear policies, faculty training, and interdisciplinary collaboration. …”
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Adaptive distributed stochastic deep reinforcement learning control for voltage and frequency restoration in islanded AC microgrids with communication noise and delay by Nima Mahdian Dehkordi, Vahab Nekoukar

“…Unlike existing distributed stochastic control methods that often fail under communication noise and variable delays, our approach dynamically adapts to these uncertainties by integrating a control Lyapunov function (CLF)-based nominal model with a deep deterministic policy gradient (DDPG) algorithm. …”
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ISCCO: a deep learning feature extraction-based strategy framework for dynamic minimization of supply chain transportation cost losses by Yangyan Li, Tingting Chen

“…This research proposed a new framework named Intelligent Supply Chain Cost Optimization (ISCCO). ISCCO integrates deep learning with advanced optimization algorithms. …”
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Recent Advances in Multi-Agent Reinforcement Learning for Intelligent Automation and Control of Water Environment Systems by Lei Jia, Yan Pei

“…Multi-agent reinforcement learning (MARL) has demonstrated significant application potential in addressing cooperative control, policy optimization, and task allocation problems in complex systems. …”
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Digital-twin driven alignment control method for marine shafting with air spring vibration isolation system by Song Liu, Liang Shi, Wei Xu, ZeChao Hu

“…Moreover, in order to achieve the optimized pressures, a soft-constrained controller based on proportional-integral-derivative (PID) algorithm is developed to accurately generate specific control policies based on the monitoring data. …”
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Artificial intelligence and criminal liability in India: exploring legal implications and challenges by Hifajatali Sayyed

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Variants of the Sliding Mode Control in Presence of External Disturbance for Quadrotor by Irfan Ahmad, Muwaida Liaquat, Fahad Mumtaz Malik, Hameed Ullah, Usman Ali

“…Firstly, a novel IIPRERL-SMC is designed through Improved Integral Sliding Mode Control (II-SMC) via proper gain scheduling by system Eigenvalues. …”
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Generative AI as a tourism actor: Reconceptualising experience co-creation, destination governance and responsible innovation in the synthetic experience economy by Evangelos Christou, Anestis Fotiadis, Antonios Giannopoulos

“…The Synthetic Experience System clarifies where value emerges, identifies points of potential value co destruction, and yields fifteen research propositions spanning tourist cognition, firm capabilities, destination policy, and planetary carbon limits. Implications: The framework provides a roadmap for destination management organisations, platform designers, and regulators to audit algorithms, design participatory prompts, and adopt carbon aware deployment. …”
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A Novel RMS-Driven Deep Reinforcement Learning for Optimized Portfolio Management in Stock Trading by Asma Sattar, Amna Sarwar, Saira Gillani, Maryam Bukhari, Seungmin Rho, Muhammad Faseeh

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ChatGPT in Education: A Systematic Review on Opportunities, Challenges, and Future Directions by Yirga Yayeh Munaye, Wasyihun Admass, Yenework Belayneh, Atinkut Molla, Mekete Asmare

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Dynamic Path Planning for Vehicles Based on Causal State-Masking Deep Reinforcement Learning by Xia Hua, Tengteng Zhang, Jun Cao

“…To address this challenge, we propose a dynamic path-planning method based on our Causal State-Masking Twin-delayed Deep Deterministic Policy Gradient (CSM-TD3) algorithm. CSM-TD3 integrates a causal inference mechanism by introducing dynamic state masks and intervention mechanisms, allowing the policy network to focus on genuine causal features for decision optimization and thereby enhancing the convergence speed and generalization capabilities of the agent. …”
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Development of Digital Training Twins in the Aircraft Maintenance Ecosystem by Igor Kabashkin

“…This paper presents an integrated digital training twin framework for adaptive aircraft maintenance education, combining real-time competence modeling, algorithmic orchestration, and cloud–edge deployment architectures. …”
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Smart Microgrid Management and Optimization: A Systematic Review Towards the Proposal of Smart Management Models by Paul Arévalo, Dario Benavides, Danny Ochoa-Correa, Alberto Ríos, David Torres, Carlos W. Villanueva-Machado

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The contingencies of platform power and risk management in the gig economy by Niels van Doorn

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