publication . Conference object . 2017

Reviewing the current state of machine learning for artificial intelligence with regards to the use of contextual information

Kinch, Martin W.; Melis, Wim J.C.; Keates, Simeon;
Open Access English
  • Published: 06 Jun 2017
  • Publisher: University of Greenwich - Faculty of Engineering & Science
  • Country: United Kingdom
This paper will consider the current state of Machine Learning for Artificial Intelligence, more specifically for applications, such as: Speech Recognition, Game Playing and Image Processing. The artificial world tends to make limited use of context in comparison to what currently happens in human life, while it would benefit from improvements in this area. Additionally, the process of transferring knowledge between application domains is another important area where artificial system can improve. Using context and transferability would have several potential benefits, such as: better ability to function in multiple problem domains, improved understanding of hum...
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