LG AI Research· EXAONEResearch paper

[AAMAS 2024] Multi-Agent Reinforcement Learning for Real-World Application (Part 1)

LG AI Research's Data Intelligence Lab presented two papers at AAMAS 2024 on multi-agent reinforcement learning for real-world applications: one on naphtha cracking center scheduling optimization and one on agent-oriented centralized critic for asynchronous MARL.

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LG AI Research’s Data Intelligence (DI) Lab presented two papers at AAMAS 2024, “Naphtha Cracking Center Scheduling Optimization using Multi-Agent Reinforcement Learning” [1] and “Agent-Oriented Centralized Critic for Asynchronous Multi-Agent Reinforcement Learning” [2]

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Announced

26 Jun 2024 00:00 UTC

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28 Aug 2026 22:20 UTC (+793d after)