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dc.contributor.authorSachse, Wolfgangen_US
dc.contributor.authorSegre, Alberto Mariaen_US
dc.contributor.authorSubramanian, Devikaen_US
dc.contributor.editorMcConkey, Gladysen_US
dc.date.accessioned2005-11-07T16:41:45Z
dc.date.available2005-11-07T16:41:45Z
dc.date.issued1989en_US
dc.identifier.urihttps://hdl.handle.net/1813/2444
dc.description.abstractIN THIS ISSUE: Machines That Learn and Recall: Their Beginnings in Research on Neural-Like Processing of Signals /2 (Wolfgang Sachse, Cornell professor of theoretical and applied mechanics, discusses how a neural-like processor can be used to analyze ultrasonic signals in materials testing.) ... Explanation-Based Learning for Machines /8 (A recent development in the field of artificial intelligence is research on machine learning that is deductive in nature and well suited to problem-solving tasks. Alberto Maria Segre, an assistant professor in Cornell's Department of Computer Science, discusses his work in this area.) ... Raising the IQ of a Robot : Reformulation of Symbolic Representations /15 (One representational law that a smart robot has to obey is: Make the fewest distinctions necessary to achieve the goal. A method of automatically obtaining this result is explained by Devika Subramanian, an assistant professor of computer science at Cornell.) ... Register /22 ... Faculty Publications /28en_US
dc.format.extent23352218 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.publisherInternet-First University Pressen_US
dc.subjectEngineeringen_US
dc.subjectCornell Universityen_US
dc.subjectneural-like processorsen_US
dc.subjectartificial intelligenceen_US
dc.subjectRobotsen_US
dc.subjectSymbolic Representationsen_US
dc.titleEngineering: Cornell Quarterly, Vol.23, No.4 (Summer 1989): Machines that Learnen_US
dc.typeperiodicalen_US


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