Multi-Agent Reinforcement Learning (MARL) is an emerging subfield of artificial intelligence that investigates how multiple autonomous agents can learn collaboratively and competitively within an ...
Multi-agent reinforcement learning (MARL) algorithms play an essential role in solving complex decision-making tasks by learning from the interaction data between computerized agents and (simulated) ...
Many real-life scenarios can be simplified and modeled using Markov decision processes (MDPs). These MDPs set an agent with available actions into a well-defined environment and let it act in there to ...
A recent study published in Engineering presents a significant advancement in manufacturing scheduling. Researchers Xueyan Sun, Weiming Shen, Jiaxin Fan, and their colleagues from Huazhong University ...
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