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LLM-Driven Social Influence for Cooperative Behavior in Multi-Agent Systems
Published 2025-01-01“…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
Published 2025-06-01“…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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Multi-Agent-Based Cognitive Intelligence in Non-Linear Mental Healthcare-Based Situations
Published 2025-01-01“…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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AI-driven multi-agent reinforcement learning framework for real-time monitoring of physiological signals in stress and depression contexts
Published 2025-06-01“…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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Bio-Inspired Traffic Pattern Generation for Multi-AMR Systems
Published 2025-03-01“…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
Published 2025-07-01“…Primary outcomes included the number of cancer cases averted, total intervention costs, and cost increase per cancer case averted. …”
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