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Enabling Multi-Agent Transfer Reinforcement Learning via Scenario Independent Representation
Multi-Agent Reinforcement Learning (MARL) algorithms are widely adopted in tackling complex tasks that require collaboration and competition among agents in dynamic Multi-Agent Systems (MAS).
MAIDCRL: Semi-centralized Multi-Agent Influence Dense-CNN Reinforcement Learning
Distributed decision-making in multi-agent systems presents difficult challenges for interactive behavior learning in both cooperative and competitive systems.
Autocompletion of Chief Complaints in the Electronic Health Records using Large Language Models
Further, we evaluate and assess the proposed models' performance and the outcome of GPT-4. 0.
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