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CAREER: AIS - An Integrated Optimization and Prediction Framework for Machine Intelligence based on Adaptive Dynamic Programming

CAREER: AIS - An Integrated Optimization and Prediction Framework for Machine Intelligence based on Adaptive Dynamic Programming
职业:AIS - 基于自适应动态规划的机器智能集成优化和预测框架
批准号:
1053717
负责人:
Haibo He
金额:
$40.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-04-01 至 2017-09-30

项目摘要

项目成果

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中文摘要
翻译
研究目标和方法:本项目的目标是推进一个新的学习框架,集成了基于自适应动态规划的优化和预测的理解,原则和应用。该方法是将参考网络集成到自适应动态规划设计中,通过提供内部增强/目标表示来连接优化和预测。所提出的架构可以设计在一个分层的方式,其中不同级别的内部强化信号可以开发代表智能系统的多层次目标。智力优势:本计画提出一个新的参考网路,以整合最佳化与预测能力,应用于类脑智能研究。这种结构提供了一种新的方法来自适应地构建内部强化信号,而不是手工制作。使用内部强化/目标表征的基本原理和数学基础可能会使认知优化和预测更接近现实。更广泛的影响:这项研究有可能为广泛的应用开发创新技术,如电网控制和通信/网络系统。除了学术界和工业界的利益外,该项目还将有利于国家和政府的利益,例如为美国能源安全和可持续发展目标提供技术创新(例如,智能电网)。综合研究和教育计划不仅将促进各级教育的卓越,而且还将丰富不同背景学生的参与,并鼓励妇女和少数民族学生进入这一领域。
英文摘要
Research Objectives and Approaches:The objective of this project is to advance the understanding, principles, and applications of a new learning framework that integrates optimization and prediction based on adaptive dynamic programming. The approach is to integrate a reference network into the adaptive dynamic programming design to link optimization and prediction by providing the internal reinforcement/goal representation. The proposed architecture can be designed in a hierarchical way, in which different levels of internal reinforcement signals can be developed to represent multi-level goals for an intelligent system. Intellectual Merit: This project proposes a new reference network to the adaptive dynamic programming design to integrate optimization and prediction capabilities for brain-like intelligence research. This structure provides a new approach to adaptively build the internal reinforcement signal rather than crafted by hand. The underlying principle and mathematical foundation of using internal reinforcement/goal representation could potentially bring cognitive optimization and prediction closer to reality. Broader Impacts: This research has the potential to develop innovative techniques for a wide range of applications, such as power grid control and communication/network systems. In addition to the benefits for academia and industry, this project will also benefit national and government interests as well, such as providing technical innovations for the U.S. energy security and sustainability objective (e.g., smart grid). The integrated research and education plan will not only promote excellence in education at different levels, but it will also enrich the participation of students with different backgrounds and encourage women and minority students to enter this field.
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Collaborative Research: Autonomous Hierarchical Adaptive Dynamic Programming for Decision Making in Complex Environment
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