A Survey on Applications of Reinforcement Learning in Spatial Resource Allocation

arXiv:2403.03643v1 Announce Type: new
Abstract: The challenge of spatial resource allocation is pervasive across various domains such as transportation, industry, and daily life. As the scale of real-world issues continues to expand and demands for real-time solutions increase, traditional algorithms face significant computational pressures, struggling to achieve optimal efficiency and real-time capabilities. In recent years, with the escalating computational power of computers, the remarkable achievements of reinforcement learning in domains like Go and robotics have demonstrated its robust learning and …

abstract algorithms applications applications of reinforcement learning arxiv challenge computational cs.ai cs.lg daily domains efficiency expand face industry life real-time reinforcement reinforcement learning scale solutions spatial survey transportation type world