LEARNING
LaMAR:面向多任务机器人专家系统的可扩展架构-奖励协同设计
Kewei Chen, Yayu Long, Mingsheng Shang
- 发表年份
- 2026
- 引用次数
- 0
- 期刊
- Expert Systems with Applications
摘要
本文提出LaMAR框架,通过协同设计架构与奖励函数,实现多任务机器人专家系统的可扩展性。该方法旨在提升机器人学习效率与泛化能力。
关键词
multi-task roboticsarchitecture-reward co-designexpert systemsscalableLaMAR
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