Online mining of human deep intention by proactive environment changes using deep neural networks

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2015

Author

Er, Nur Baki

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This thesis focuses on surfacing human deep intention, which is known or assumed, in a smart environment that consists of autonomous robotic systems which can interact with the human. Deep intentions are defined as kind of actions that humans would like to behave but pushed deeper in the stack of the intentions in a daily life. The purpose of the designed system is to observe the human in the smart room for a while and to analyze human’s behaviors to offer the optimal set of system behavior to surface a desired deep intention. Deep neural networks classify people implicitly by trained deep learning architecture and outputs the set of system behaviors to trigger deep intention. The autoencoders implemented in the network generate better and compressed representation of input vectors by creating feature vectors without using any feature extraction method. In addition autoencoders also enable the system to have better initialized parameters. This thesis work introduces our novel approach of surfacing human deep intention by utilizing human robot interaction in a smart environment.

Subject Keywords

Human-robot interaction., Neural networks (Computer science)., Expert systems (Computer science)., Intention (Logic)., Machine learning., Artificial intelligence.

URI

http://etd.lib.metu.edu.tr/upload/12619664/index.pdf
https://hdl.handle.net/11511/25573

Collections

Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

N. B. Er, “Online mining of human deep intention by proactive environment changes using deep neural networks,” M.S. - Master of Science, Middle East Technical University, 2015.