Artificial intelligence is the study of intelligence agents as demonstrated by machines. It is an interdisciplinary field involving computer science as well as, various kinds of engineering and science, for example, robotics, bio-medical engineering, that accentuates automation of human acts and intelligence through machines. AI represents state-of-the-art use of machines to bring about algorithmic computation and understanding of tasks that include learning, problem solving, mapping, perception, and reasoning. Given the data and a description of its properties and relations between objects of interest, AI methods can perform the aforementioned tasks. Widely applied AI capabilities, e.g. learning, are now achievable at large scale through machine learning (ML), large volumes of data and specialized computational machines. ML encompasses learning without any kind of supervision (unsupervised learning) and learning with full supervision (supervised learning). Widely applied supervised learning techniques include deep learning and other machine learning methods that require less data than deep learning e.g. support vector machines, random forests. Unsupervised learning examples include dictionary learning, independent component analysis, and autoencoders. For application tasks with less labeled data, both supervised and unsupervised techniques can be adapted in a semi-supervised manner to produce accurate models and to increase the size of the labeled training data.
Computing Platforms provide the computational capabilities to apply methods and models to geographic data. Computing Platforms vary in capability, price, and availability from mobile devices to advanced supercomputers and from standalone computers to complex networked infrastructures to address different user needs and data-processing workloads.
Topics in this Knowledge Area are listed thematically below. Existing topics are in regular font and linked directly to their original entries (published in 2006; these contain only Learning Objectives). Entries that have been updated and expanded are in bold. Forthcoming, future topics are italicized.
|Computing Infrastructures||Software Systems|
|Graphics Processing Units||Spatial Database Management Systems (DBMS)|
|Spatial Cloud Computing||Spatial MapReduce|
|Mobile Devices||Artificial Intelligence Tools and Platforms for GIS|
|Cyberinfrastructure||Geospatial Technology Transfer Opportunities|
|Computing Approaches||Enterprise GIS|
|Origins of Computing & GIS&T: a Computer Systems Perspective|
|Origins of Computing & GIS&T: a Perspective on the Role of Peripheral Devices||Examples and Applications|
|High Throughput Computing and GIS||Google Earth Engine|
|High Performance Computing and GIS||ArcGIS Online|
|GIS&T and Grid Computing||GIS&T and Computational Notebooks|
|Science Gateways||GIS&T and Amazon Web Services|
|Social Media and Location-based Services|
|GIS& the Internet of Things|
|Social Media Analytics|
|GIS&T Web Services|