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》 资源 》论文》Decision-Making Under Uncertainty in Multi-Agent and Multi-Robot Systems: Planning and Learning

Decision-Making Under Uncertainty in Multi-Agent and Multi-Robot Systems: Planning and Learning

2019-11-06 | |  50 |   45 |   0
Abstract Multi-agent planning and learning methods are becoming increasingly important in today’s interconnected world. Methods for real-world domains, such as robotics, must consider uncertainty and limited communication in order to generate highquality, robust solutions. This paper discusses our work on developing principled models to represent these problems and planning and learning methods that can scale to realistic multi-agent and multirobot tasks.

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