CAREER: Activity Discovery for Programmable & Adaptive Personalized Environments

职业：可编程活动发现

• 批准号: 0644206
• 负责人: Charles Isbell
• 金额: $ 50万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-02-01 至 2012-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0644206&HistoricalAwards=false
• 关键词: CAREER; Activity; Discovery; Programmable; &amp

The intent of this research project is to support adaptive and personalized information environments. Central to this vision is the need to improve activity discovery and representation of user behavior. This will necessitate the development of novel machine learning algorithms for building models of that activity. (An extension of the ABL agent language with support for looping prediction suffix trees is proposed.) This approach will be applied to two innovative domains, user interactions with smart appliances and semi-autonomous agents in online gaming environments.

这个研究项目的目的是支持自适应和个性化的信息环境。这个愿景的核心是需要改进活动发现和用户行为的表示。这将需要开发新的机器学习算法来构建该活动的模型。（提出了ABL代理语言的扩展，支持循环预测后缀树。）这种方法将应用于两个创新领域，即用户与智能设备的交互和在线游戏环境中的半自主代理。