LEARNING
SCALE-COMM:用于多智能体强化学习通信的共享对比对齐潜在嵌入
Mahmoud Abouelyazid, Eman Hammad
- 发表年份
- 2026
- 访问权限
- 开放获取
摘要
本文提出SCALE-COMM框架,通过自监督学习解耦通信与策略优化,生成紧凑、稳定且与任务相关的潜在消息。实验表明,该方法在标准基准和仓库协调任务中显著提升了通信表示质量和任务性能。
关键词
multi-agent reinforcement learningemergent communicationcontrastive learninglatent embeddingsautonomous mobile robots
相关论文
LEARNING
📊 8,465 引用
The Organization of Behavior
D. O. Hebb
2005
LEARNING
📊 7,678 引用
Fractional Brownian Motions, Fractional Noises and Applications
Benoît B. Mandelbrot, John W. Van Ness
1968
LEARNING
开放获取📊 7,484 引用
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
Laith Alzubaidi, Jinglan Zhang, Amjad J. Humaidi 等 10 位作者
2021
LEARNING
📊 4,608 引用
A guide to deep learning in healthcare
Andre Esteva, Alexandre Robicquet, Bharath Ramsundar 等 10 位作者
2018