RI: Medium: Collaborative Research: Optimizing Policies for Service Organizations in Complex Structured Domains
RI: Medium: Collaborative Research: Optimizing Policies for Service Organizations in Complex Structured Domains
批准号:
0964705
负责人:
Prasad Tadepalli
金额:
$58.17万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-07-01 至 2015-06-30
中文摘要
该项目使用模拟器和概率模型研究一类重要的复杂结构化规划领域,称为“服务领域”。服务域的示例包括优化典型城市的紧急响应,调度医院的医生和护士,管理典型办公室的任务,以及从配送中心向商店提供最佳产品。这些领域具有许多共同的特征,如关系结构,并行操作,多时间尺度决策,外生事件,以及对人类可解释解决方案的需求,这使得它们具有高度的挑战性。该项目通过各种技术,包括多时间尺度优化的新层次框架,新的无模型基于仿真的规划算法,以及通过一阶决策图的合成的基于模型的规划。这些技术被应用到现实世界的问题,优化火灾和应急响应的城市通过与科瓦利斯,俄勒冈州消防部门的合作。该项目的成果包括新的算法和框架来解决服务域,原型实现的算法在紧急响应域,和新的测试床的服务域的研究。这项工作的更广泛影响包括更具有成本效益的应急系统,以及开发新的面向研究的课程、教程和关于服务领域下一代决策支持系统的特别讲习班。
英文摘要
This project studies an important class of complex structured planning domains called ``service domains'' using simulators and probabilisticaction models. Examples of service domains include optimizing emergency response in a typical city, scheduling doctors and nurses in a hospital, administering tasks in a typical office, optimally delivering products to shops from distribution centers. These domains share many characteristics such as relational structure, parallel actions, multi-time-scale decision making, exogenous events, and the need for human interpretable solutions that make them highly challenging.The project develops scalable and principled planning algorithms for service domains through a variety of techniques including a novelhierarchical framework of multi-time-scale optimization, newmodel-free simulation-based planning algorithms, and model-based planning via composition of first-order decision diagrams. These techniques are applied to the real-world problem of optimizing the fire and emergency response in cities through a collaborationwith the fire department of Corvallis, Oregon. The results of the project include new algorithms and frameworks to solve service domains, prototype implementations of the algorithmsin the emeregency response domain, and new testbeds of service domains for research. The broader impact of the work includes more cost-effective emergency response systems, and development of new research-oriented courses, tutorials and special workshops on the next generation decision support systems for service domains.
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