APPA: An adaptation path planning algorithm for real-time obstacle avoidance in multi-robot systems by Jianzhi Jin, Mou Wu, Ping Fan, Guonian Jin

“…Experimental results show that APPA significantly outperforms baseline algorithms such as ORCA, ALAN, and PRIMAL. While deep reinforcement learning approaches like ALAN excel in static environments through neural network-based policy learning, APPA’s non-parametric uncertainty modeling provides superior adaptability in dynamic scenarios with unpredictable obstacle patterns, achieving 94% success rate compared to ALAN’s 52% in high-density dynamic environments. …”
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Design of an efficient dynamic context‐based privacy policy deployment model via dual bioinspired Q learning optimisations by Namrata Jiten Patel, Ashish Jadhav

“…Abstract A novel context‐based privacy policy deployment model enhanced with bioinspired Q‐learning optimisations is presented. …”
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Integrating Visual Cryptography for Efficient and Secure Image Sharing on Social Networks by Lijing Ren, Denghui Zhang

“…While standard encryption algorithms can safeguard the privacy of textual data, image data entail larger volumes and significant redundancy. …”
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A Systematic Literature Review on Sustainability Integration and Marketing Intelligence in the Era of Artificial Intelligence by Md Mehedi Hasan Emon, Tahsina Khan

“…The purpose of the study is to explore Artificial intelligence (AI) integration into sustainable marketing techniques highlights a transformational potential, combining modern technology with the urgent needs of sustainability. …”
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Learning-based control for tendon-driven continuum robotic arms by Nima Maghooli, Omid Mahdizadeh, Mohammad Bajelani, S. Ali A. Moosavian

“…This paper presents a centralized position control strategy using Deep Reinforcement Learning, with a particular focus on the Sim-to-Real transfer of control policies. The proposed method employs a customized Modified Transpose Jacobian control strategy for continuum arms, where its parameters are optimally tuned using the Deep Deterministic Policy Gradient algorithm. …”
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The use of deep learning algorithm and digital media art in all-media intelligent electronic music system. by Yingming Zheng

“…In the development of digital media art, to explore the preliminary application of deep learning method in intelligent electronic music system, and promote the integration of deep learning method and digital media technology, thus providing a direction for the development of all media intelligent system, based on deep deterministic policy gradient (DDPG), to solve the multi-task problem in intelligent system, a multi-task learning-based DDPG algorithm (M-DDPG) is proposed. …”
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The joint policy of production, maintenance, and product quality in a multi-machine production system by reinforcement learning and agent-based modeling by Mohammad Reza Nazabadi, Seyed Najafi, Ali Mohaghar, Farzad Movahedi Sobhani

“…The production system studied in this research has been modeled using the agent-based simulation, and the Reinforcement Learning (RL) algorithm has obtained the optimal integrated policy. …”
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MODERN TRENDS IN INNOVATIVE DEVELOPMENT OF EDUCATIONAL SERVICES FOR FOREIGN CITIZENS IN THE INTEGRATED ENVIRONMENT by I. V. Medynskaya

“…The current stage of scientific and technological progress and digital revolution development demonstrates the priority of export of educational services for the increase of foreign policy, foreign economic and cultural relations between countries. …”
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Beamforming and resource optimization in UAV integrated sensing and communication network with edge computing by Bin LI, Sicong PENG, Zesong FEI

“…To address the dependence of traditional integrated sensing and communication network mode on ground infrastructure, the unmanned aerial vehicle (UAV) with edge computing server and radar transceiver was proposed to solve the problems of high-power consumption, signal blocking, and coverage blind spots in complex scenarios.Firstly, under the conditions of satisfying the user’s transmission power, radar estimation information rate and task offloading proportion limit, the system energy consumption was minimized by jointly optimizing UAV radar beamforming, computing resource allocation, task offloading, user transmission power, and UAV flight trajectory.Secondly, the non-convex optimization problem was reformulated as a Markov decision process, and the proximal policy optimization method based deep reinforcement learning was used to achieve the optimal solution.Simulation results show that the proposed algorithm has a faster training speed and can reduce the system energy consumption effectively while satisfying the sensing and computing delay requirements.…”
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An Integrated Approach to Scheduling B-CAVs in Container Terminals considering Battery Management by Shuo Wang, Jiliang Luo, Weimin Wu, Dahai Zhang, Tao Zhang

“…Then, a sustainable charging policy is designed to ensure the consistent transport capacity of an HTS. …”
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Soft actor-critic algorithm and improved GNN model in secure access control of disaggregated optical networks by Zhenqian Zhao, Yuhe Wang

“…Within this framework, the Soft Actor-Critic (SAC) algorithm is employed to construct a policy optimization mechanism. …”
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Integrated Waste Management in the Circular Economy Era: Insights from Research and Practice by Charisios Achillas, Christos Vlachokostas

“…Technological advancements, such as AI-driven waste sorting and route optimization algorithms, are highlighted alongside policy frameworks supporting circular economy principles. …”
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Efficient TD3 based path planning of mobile robot in dynamic environments using prioritized experience replay and LSTM by Yunhan Lin, Zhijie Zhang, Yijian Tan, Hao Fu, Huasong Min

“…Abstract To address the challenges of sample utilization efficiency and managing temporal dependencies, this paper proposes an efficient path planning method for mobile robot in dynamic environments based on an improved twin delayed deep deterministic policy gradient (TD3) algorithm. The proposed method, named PL-TD3, integrates prioritized experience replay (PER) and long short-term memory (LSTM) neural networks, which enhance both sample efficiency and the ability to handle time-series data. …”
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Protocol for validating an algorithm to identify neurocognitive disorders in Canadian Longitudinal Study on Aging participants: an observational study by Verena Menec, Teresa Liu-Ambrose, David B Hogan, Megan E O’Connell, Mary Thompson, Andrew P Costa, Eric E Smith, Changbao Wu, Aaron Jones, Andrew Wister, Christina Wolfson, Parminder Raina, Jinhui Ma, Lauren E Griffith, Christopher Patterson, Alexandra J Mayhew, Benoit Cossette, David Hogan, Howard Chertkow, Susan Kirkland, Megan O'Connell, Vanessa Taler, Andrew Costa, Jacqueline McMillan, Gerry Mugford, Theone Paterson

“…Sensitivity, specificity, the C-statistic and the phi coefficient will also be estimated.Ethics and dissemination Ethics approval has been received from the institutional research ethics boards for each CLSA Data Collection Site (Université de Sherbrooke, Hamilton Integrated Research Ethics Board, Dalhousie University, Nova Scotia Health Research Ethics Board, University of Manitoba, McGill University, McGill University Health Centre Research Institute, Memorial University of Newfoundland, University of Victoria, Élisabeth Bruyère Research Institute of Ottawa, University of British Columbia, Island Health (Formerly the Vancouver Island Health Authority, Simon Fraser University, Calgary Conjoint Health Research Ethics Board).The results of this work will be disseminated to public health professionals, researchers, health professionals, administrators and policy-makers through journal publications, conference presentations, publicly available reports and presentations to stakeholder groups.…”
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Integrating Moral Values in AI: Addressing Ethical Challenges for Fair and Responsible Technology by Khushboo Shah, Hiren Joshi, Hardik Joshi

“…Here author has proposed a new model named Ethical Alignment Algorithm (EAA). This model helps to integrate ethics with AI step-by-step. …”
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Integrating microplastic research in sustainable agriculture: Challenges and future directions for food production by Marcelo Illanes, María-Trinidad Toro, Mauricio Schoebitz, Nelson Zapata, Diego A. Moreno, María Dolores López-Belchí

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Use of responsible artificial intelligence to predict health insurance claims in the USA using machine learning algorithms by Ashrafe Alam, Victor R. Prybutok

“…The algorithms examined include support vector machine (SVM), decision tree (DT), random forest (RF), linear regression (LR), extreme gradient boosting (XGBoost), and k-nearest neighbors (KNN). …”
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Research on the impact of the integration of digital economy and real economy on China’s domestic value chain resilience by Chunhui Huo, Shengkai Bian, Di He, Mengxiao Lv

“…Conclusions These conclusions underscore the necessity of developing and innovating digital-real economy integration policies centered on stabilizing and strengthening value chains, thereby enhancing the intrinsic dynamism and reliability of domestic value chains.…”
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Analyzing cropland fragmentation evolution and driving mechanisms in Shandong through MSPA and landscape metrics integration by Tianwei Zhang, Wei Li, Zengfeng Zhao, Meizhen Bi, Yi Zheng

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Ethical Challenges and Opportunities of AI in End-of-Life Palliative Care: Integrative Review by Abel García Abejas, David Geraldes Santos, Fabio Leite Costa, Aida Cordero Botejara, Helder Mota-Filipe, Àngels Salvador Vergés

“… BackgroundArtificial intelligence (AI) is increasingly integrated into palliative medicine, offering opportunities to improve quality, efficiency, and patient-centeredness in end-of-life care. …”
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