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Towards a Reading Coach that Listens: Automated Detection of Oral Reading Errors

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Proceedings of the Eleventh National Conference on Artificial Intelligence (AAAI93), American Association for Artificial Intelligence, Washington, DC, July 1993, pp. 392-397.


Neural Network Perception for Mobile Robot Guidance

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Vision based mobile robot guidance has proven difficult for classical machine vision methods because of the diversity and real time constraints inherent in the task. This thesis describes a connectionist system called ALVINN (Autonomous Land Vehicle In a Neural Network) that overcomes these difficulties. ALVINN learns to guide mobile robots using the back-propagation training algorithm. Because of its ability to learn from example, ALVINN can adapt to new situations and therefore cope with the diversity of the autonomous navigation task. But real world problems like vision based mobile robot guidance presents a different set of challenges for the connectionist paradigm.


Statistical Language Learning

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MIT Press. See also: Review of "Statistical language learning" by Eugene Charniak (http://europepmc.org/abstract/CIT/136037).


On Seeing Robots

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. It is argued that Situated Agents should be designed using a unitaryon-line computational model. The Constraint Net model of Zhang and Mackworth satisfiesthat requirement. Two systems for situated perception built in our laboratory are describedto illustrate the new approach: one for visual monitoring of a robot’s arm, the other forreal-time visual control of multiple robots competing and cooperating in a dynamic world.First proposal for robot soccer.Proc. VI-92, 1992. later published in a book Computer Vision: System, Theory, and Applications, pages 1-13, World Scientific Press, Singapore, 1993.