# LG AI Research — [AAMAS 2024] Multi-Agent Reinforcement Learning for Real-World Application (Part 1)

- Company: LG AI Research (lgresearch.ai)
- Announced: 2024-06-26T00:00:00+00:00
- Category: research-paper
- Subject: EXAONE
- Source: https://www.lgresearch.ai/blog/view?seq=444
- Record: https://forck.live/items/4847-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.

## Evidence

Verbatim from https://www.lgresearch.ai/blog/view?seq=444:

> 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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Record: https://forck.live/items/4847-aamas-2024-multi-agent-reinforcement-learning-for-real-world-application-part-1
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