基于数据/知识的系统控制策略选择的反馈镇定

C. Starmer
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引用次数: 1

摘要

基于知识和/或数据的决策支持系统可以被视为复杂的控制系统,旨在优化期望的标准。因此,它们通过应用适当的控制策略帮助用户将具有初始状态向量的对象转换为某些期望的结果状态。系统有效性可以通过决策错误的数量来衡量。通过将系统使用实例数据库与知识库的实现相结合,可以促进知识库的完整性和有效性。系统使用的实例被视为应该与知识库一致的跟踪。数据库包含描述系统使用的每个实例的记录(跟踪),并包括被控制对象的状态向量、选择的控制策略和最终的结果状态向量。控制策略的稳定性在决策过程中得到改善,通过纳入反馈数据路径,该路径来源于控制策略应用的实际结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Feedback stabilization of control policy selection in data/knowledge based systems
Knowledge and/or data-based decision support systems can be viewed as complex control systems designed to optimize a desired criterion. As such, they aid users in transforming objects with an initial state vector to some desired outcome state by application of a suitable control policy. System effectiveness can be measured by the number of decision errors. Completeness and validity of the knowledge base can be facilitated by coupling a database of instances of system use with the implementation of the knowledge base. Instances of system use are viewed as traces which should be consistent with the knowledge base. The database contains records characterizing each instance of system use (a trace) and includes the state vector of the object being controlled, the selected control strategy, and the resultant outcome state vector. Stability of control policies is improved within the decision process by incorporating a feedback data path that is derived from actual outcomes resulting from application of a control policy.
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