Agent-based Intelligent Messaging Systems, Natural Language Generation, Markov Decision Processes, Verification, Machine Learning

基于代理的智能消息系统、自然语言生成、马尔可夫决策过程、验证、机器学习

• 批准号: 520347-2017
• 负责人: Bentahar, Jamal
• 金额: $ 4.48万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=645200
• 关键词: Agent; based; Intelligent; Messaging; Systems

This project addresses the design and development of an intelligent messaging system used as an interactive tutoring module. The objectives of the project are: (1) to specify, develop, and verify software design of the rational agents to deploy Natural Language Generation (NLG) while interacting with human learners; (2) develop real-time decision making and reinforcement learning to empower agents to better interact with learners and carry on a productive conversation; and (3) enable intelligent guidance and perform real time messaging mechanisms that effectively navigate through a logic decision tree.

该项目介绍了用作交互式辅导模块的智能消息系统的设计和开发。该项目的目标是：（1）在与人类学习者互动时指定，开发和验证理性代理的软件设计以部署自然语言生成（NLG）； （2）开发实时决策和强化学习，以使代理人能够更好地与学习者互动并进行富有成效的对话； （3）启用智能指导并执行有效浏览逻辑决策树的实时消息传递机制。