QMIX-GNN: A Graph Neural Network-Based Heterogeneous Multi-Agent Reinforcement Learning Model for Improved Collaboration and Decision-Making
In multi-agent reinforcement learning, the fully centralized approach suffers from issues such as explosion of the joint state and action spaces, leading to performance degradation. On the other hand, the fully decentralized approach relies on agents that focus solely on maximizing their own rewards...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/7/3794 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Be the first to leave a comment!