A Hierarchical Reinforcement Learning Framework for Multi-Agent Cooperative Maneuver Interception in Dynamic Environments by Qinlong Huang, Yasong Luo, Zhong Liu, Jiawei Xia, Ming Chang, Jiaqi Li

“…To address the challenges of real-time decision-making and resource optimization in multi-agent cooperative interception tasks within dynamic environments, this paper proposes a hierarchical framework for reinforcement learning-based interception algorithm (HFRL-IA). …”
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LLM-Driven Social Influence for Cooperative Behavior in Multi-Agent Systems by J. de Curto, I. de Zarza

“…This paper presents a novel approach to fostering cooperative behavior in multi-agent systems (MAS) through Large Language Model (LLM)-driven social influence. …”
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Information coevolution spreading model and simulation based on self-organizing multi-agents by Guoxin Ma, Kang Tian, Hongbo Sun, Hong Zhao, Yongyan Wang

“…These findings provide actionable insights for controlling misinformation in social networks and optimizing public health interventions, emphasizing that "more intervention" does not always equate to "better control" in coevolutionary systems.…”
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A cooperative jamming decision-making method based on multi-agent reinforcement learning by Bingchen Cai, Haoran Li, Naimin Zhang, Mingyu Cao, Han Yu

“…Abstract Electromagnetic jamming is a critical countermeasure in defense interception scenarios. This paper addresses the complex electromagnetic game involving multiple active jammers and radar systems by proposing a multi-agent reinforcement learning-based cooperative jamming decision-making method (MA-CJD). …”
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Multi-Agent-Based Cognitive Intelligence in Non-Linear Mental Healthcare-Based Situations by Kiran Saleem, Misbah Saleem, Ahmad Almogren, Alanod Almogren, Upinder Kaur, Salil Bharany, Ateeq Ur Rehman

“…This study introduces a novel framework for the early detection of anxiety and depression symptoms through the integration of Ambient Intelligence (AmI) and Multi-Agent Systems (MAS). Leveraging a Belief-Desire-Intention (BDI) reasoning mechanism, our system enables real-time monitoring and intervention with high precision. …”
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ResilioMate: A Resilient Multi-Agent Task Executing Framework for Enhancing Small Language Models by Yubing Xiong, Mingrui Huang, Xuechen Liang, Meiling Tao

“…ResilioMate accomplishes three critical improvements: 1) The 1.8B LeptoConnect model attains 81.6% of GPT-4’s performance in knowledge graph construction through parameter-efficient fine-tuning with structured weight matrices; 2) LeptoConnect-7B achieves a score of 41.3 in database operations, compared to GPT-4’s 32.0, through collaborative cognitive load allocation; and 3) A bias-interception network effectively suppresses adversarial propagation while achieving code correction performance of ROUGE-L’s 42.86. …”
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AI-driven multi-agent reinforcement learning framework for real-time monitoring of physiological signals in stress and depression contexts by Thanveer Shaik, Xiaohui Tao, Lin Li, Haoran Xie, Hong-Ning Dai, Feng Zhao, Jianming Yong

“…Abstract Purpose Effective patient monitoring is crucial for timely healthcare interventions and improved outcomes, especially in managing conditions influenced by stress and depression, which can manifest through physiological changes. …”
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A Class of Perimeter Defense Strategies Based on Priority Path Planning by Shuang Zhang, Chengqian Yang, Shiwei Lin, Bomin Huang

“…This paper investigates perimeter defense strategies for multi-agent systems. Considering the complex scenario with multiple obstacles in the mission environment, a defense strategy based on prioritized path planning is proposed in this paper. …”
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Exploring the possibilities of MADDPG for UAV swarm control by simulating in Pac-Man environment by Artem Novikov, Sergiy Yakovlev, Ivan Gushchin

“…Future research should focus on comparing the effectiveness of MADDPG-trained models with multi-agent algorithms, such as Expectimax, Alpha-Beta Pruning, and Monte Carlo Tree Search (MCTS), to further understand the advantages and limitations of learning-based approaches compared with traditional decision-making methods in collaborative and adversarial UAV operations. …”
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Bio-Inspired Traffic Pattern Generation for Multi-AMR Systems by Rok Vrabič, Andreja Malus, Jure Dvoršak, Gregor Klančar, Tena Žužek

“…Validated through physics-based simulations in Gazebo across three scenarios, a standard MAPF benchmark, and two industrial environments, the movement constraints generated using the proposed method improved the system throughput by up to 10% compared to unconstrained navigation and up to 4% compared to expert-designed solutions while reducing the need for conflict-resolution interventions.…”
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HPV DNA screening and vaccination strategies in Tunisia by Anas Lahdhiri, Beya Benzina, Emna Ennaifer, Haifa Tounsi, Ahlem Gzara, Soumaya Rammeh-Rommani, Oumaima Laraj, Heger Arfaoui, Robyn Stuart, Amira Kebir, Slimane BenMiled

“…Primary outcomes included the number of cancer cases averted, total intervention costs, and cost increase per cancer case averted. …”
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