Engineering Artificial Intelligence: A Spatial Representation and Reasoning Perspective

工程人工智能：空间表示和推理的视角

• 批准号: FT0991917
• 负责人: Prof Dr Jochen Renz
• 金额: $ 56.26万
• 依托单位: The Australian National University
• 依托单位国家: 澳大利亚
• 项目类别: ARC Future Fellowships
• 财政年份: 2010
• 资助国家: 澳大利亚
• 起止时间: 2010-04-20 至 2014-04-19
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FT0991917
• 关键词: Engineering; Artificial; Intelligence; Spatial; Representation

Spatial information is important in areas of national interest such as mining and exploration, environmental monitoring and planning, emergency response, and defence. Mission control centres, for instance, receive different forms of spatial data from satellites, radar, or people on the ground. They have to process the input data and make intelligent decisions in a very limited time. Intelligent systems that are able to assist with processing different forms of spatial data efficiently and that offer reliable decision support are essential for improving the quality and reliability of such applications. This research enables future intelligent systems with these capabilities. This will directly benefit applications in areas of national interest.

空间信息在采矿和勘探、环境监测和规划、应急响应和国防等国家利益领域非常重要。例如，任务控制中心从卫星、雷达或地面人员接收不同形式的空间数据。他们必须在非常有限的时间内处理输入数据并做出明智的决策。能够帮助有效处理不同形式的空间数据并提供可靠决策支持的智能系统对于提高此类应用的质量和可靠性至关重要。这项研究使未来的智能系统具备这些功能。这将直接有利于国家利益领域的应用。