首页> 外文会议>International Workshop on Graph Structures for Knowledge Representation and Reasoning >Creative Composition Problem:A Knowledge Graph Logical-Based AIConstruction and Optimization Solution Applied in Cecilia: An Architecture of a Digital CompanionArtificial Intelligence (AI) Agent System Composer of DialogueScripts for Well-Being and Mental Health
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Creative Composition Problem:A Knowledge Graph Logical-Based AIConstruction and Optimization Solution Applied in Cecilia: An Architecture of a Digital CompanionArtificial Intelligence (AI) Agent System Composer of DialogueScripts for Well-Being and Mental Health

机译:创意作文问题:在塞西莉亚应用了知识图形的基于逻辑的逻辑AICOnstruction和优化解决方案:用于福祉和心理健康的对话的数字公司人工智能(AI)代理系统作曲家的架构

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Contribution of this work is to Define the Creative Composition Prob-lem (CCP) for Human Well-being Optimization by Construction of Knowledge Graph using Knowledge Representation and logic-based Artificial Intelligence reasoning-planning where the computation of the Optimal Solution is achieved by Dynamic Programming or Logic Programming. The Creative Composition Problem is embedded within Cecilia: an architecture of a digital companion arti-ficial intelligence agent system composer of dialogue scripts for Well-being and Mental Health. Where Cecilia Framework is instantiated in Well-being and Men-tal Health domain for optimal well-being development of first year university stu-dents. We define the "The Problem of Creating a Dialogue Composition (PCDC)' and we propose a feasible and optimal solution of it. CCP is instantiated in this applied domain to solve PCDC optimizing the Mental Health and Well-being of the student. CCP as PCDC is applied to optimize maximizing the mental health of the student but also maximizing the smoothness, coherence, enjoyment and engagement each time the dialogue session is composed. Cecilia helps students to manage stress/anxiety to attempt the prevention of depression. Students can interact through the digital companion making questions and answers. While the system "learns" from the user it allows the user to learn from herself. Once the student discovers elements that were unnoticed by her, she will find a better way to improve when discovering her points of improvement.
机译:这项工作的贡献是通过使用知识表示和基于逻辑的人工智能推理规划的知识图来定义人类富裕优化的创意作品Prob-LEM(CCP),其中通过动态实现最佳解决方案的计算编程或逻辑编程。创意作文问题嵌入塞西利亚:福祉和心理健康的对话脚本的数字伴奏艺术智力代理系统作曲家的体系结构。塞西莉亚框架在福祉和男性健康领域实例化,以获得第一年大学斯图顿的最佳发展。我们定义“创建对话构成(PCDC)”的问题,我们提出了一种可行和最佳的解决方案。CCP在这个应用的域中实例化,以解决PCDC优化学生的心理健康和福祉。CCP AS PCDC适用于优化学生的心理健康,而且每次组成对话会议时也会最大限度地提高学生的心理健康。Cecilia帮助学生管理压力/焦虑以尝试预防抑郁症。学生可以通过数字伴侣制作问题和答案。虽然系统从用户“学习”它允许用户从自己学习。一旦学生发现了她所忽视的元素,她就会找到更好的方法来发现她的观点改进。

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