摘要
资源优化问题广泛存在于社会、经济的运转中,积累了海量的数据,给强化学习技术在这一领域的应用奠定了基础。由于资源优化问题覆盖广泛,从覆盖广泛的资源优化问题中划分出3类重要问题,即资源平衡问题、资源分配问题和装箱问题。并围绕这3类问题总结强化学习技术的最新研究工作,围绕各研究工作的问题建模、智能体设计等方面展开详细阐述。
Resource optimization is an important problem that widely exists in the social operation and economic development.There is massive data accumulated in this field which has laid the foundation for more and more application of reinforcement learning.Due to the wide coverage of resource optimization problems,three important problems from the wide range of resource optimization problems were categorized and chosen,namely resource balancing problem,resource allocation problem,and bin packing problem.The problem formulation and the reinforcement learning agent modeling of these three types of problems were introduced in detail.
作者
王金予
魏欣然
石文磊
张佳
WANG Jinyu;WEI Xinran;SHI Wenlei;ZHANG Jia(Microsoft Research Asia,Beijing 100080,China)
出处
《大数据》
2021年第5期131-149,共19页
Big Data Research
关键词
强化学习
资源优化
多智能体系统
reinforcement learning
resource optimization
multi-agent system