Date of Award

1-1-2010

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Information Science

Content Description

1 online resource (viii, 151 pages) : illustrations (some color)

Dissertation/Thesis Chair

Andrew R. Haas

Committee Members

Istvan Kecskes, Neil V. Murray, Kevin H. Knuth

Keywords

computational linguistics, embodied cognition, Hausser, pragmatics, robots, Natural language processing (Computer science), Semantic computing, Computational linguistics, Robotics

Subject Categories

Artificial Intelligence and Robotics | Library and Information Science | Linguistics

Abstract

Computational natural language understanding and generation have been a goal of artificial intelligence since McCarthy, Minsky, Rochester and Shannon first proposed to spend the summer of 1956 studying this and related problems. Although statistical approaches dominate current natural language applications, two current research trends bring renewed focus on this goal. The nascent field of artificial general intelligence (AGI) seeks to evolve intelligent agents whose multi-subagent architectures are motivated by neuroscience insights into the modular functional structure of the brain and by cognitive science insights into human learning processes. Rapid advances in cognitive robotics also entail multi-agent software architectures that attempt to parallel in many ways the sensory and cognitive processes of humans. Natural language capability is a key objective for both types of software, whether embodied in a physical robot or in a virtual world that emulates features of the physical environment.

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