The Role of Blackboard-Based Reasoning and Visual Analytics in RESIN's Predictive Analysis

D. Liu, Jia Yue, Xiaoyu Wang, A. Raja, W. Ribarsky
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引用次数: 5

Abstract

Knowledge gathering and investigative tasks in open environments can be very complex because the problem-solving context is constantly evolving, and the data may be incomplete, unreliable and/or conflicting. This paper significantly extends our previous work on a mixed-initiative agent by making it capable of assisting humans in foraging task analysis using AI blackboard-based reasoning, visualizations and a mix-initiative user interface. The agent is equipped with the ability to adapt its processing to available resources, deadlines and its current problem-solving context.
基于黑板的推理和可视化分析在树脂预测分析中的作用
在开放环境中,知识收集和调查任务可能非常复杂,因为解决问题的环境不断变化,数据可能不完整、不可靠和/或相互冲突。本文极大地扩展了我们之前在混合主动代理上的工作,使其能够使用基于AI黑板的推理、可视化和混合主动用户界面来协助人类进行任务分析。代理具有使其处理适应可用资源、最后期限和当前解决问题的上下文的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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