Large Markov decision processes and combinatorial optimisation

大马尔可夫决策过程和组合优化

• 批准号: DP220102101
• 负责人: Dr Ali Eshragh
• 金额: --
• 依托单位: The University of Newcastle
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2022
• 资助国家: 澳大利亚
• 起止时间: 2022-01-01 至 2023-03-22
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP220102101
• 关键词: Large; Markov; decision; processes; combinatorial

Markov decision processes continue to gain in popularity for modelling a wide range of applications ranging from analysis of supply chains and queueing networks to cognitive science and control of autonomous vehicles. Nonetheless, they tend to become numerically intractable as the size of the model grows fast. Recent works use machine learning techniques to overcome this crucial issue, but with no convergence guarantee. This project aims to provide theoretically sound frameworks for solving large Markov decision processes, and exploit them to solve important combinatorial optimisation problems. This timely project can promote Australia's position in the development of such novel frameworks for many scientific and industrial applications.

马尔可夫决策过程继续在建模广泛的应用中越来越受欢迎，从供应链和网络分析到认知科学和自动驾驶汽车控制。尽管如此，随着模型规模的快速增长，它们往往变得难以处理。最近的工作使用机器学习技术来克服这个关键问题，但没有收敛保证。该项目旨在为解决大型马尔可夫决策过程提供理论上合理的框架，并利用它们来解决重要的组合优化问题。这一及时的项目可以促进澳大利亚在许多科学和工业应用中开发这种新框架的地位。