CuMARL: Curiosity-Based Learning in Multiagent Reinforcement Learning
In this paper, we propose a novel curiosity-based learning algorithm for Multi-agent Reinforcement Learning (MARL) to attain efficient and effective decision-making. We employ the centralized training with decentralized execution framework (CTDE) and consider that each agent has knowledge of the pri...
| Main Authors: | , , , , |
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| פורמט: | Article |
| שפה: | English |
| יצא לאור: |
IEEE
2022-01-01
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| סדרה: | IEEE Access |
| נושאים: | |
| גישה מקוונת: | https://ieeexplore.ieee.org/document/9857920/ |