AAAI Publications, Thirty-First AAAI Conference on Artificial Intelligence

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Natural Language Dialogue for Building and Learning Models and Structures
Ian Perera, James F. Allen, Lucian Galescu, Choh Man Teng, Mark Burstein, Scott Friedman, David McDonald, Jeffrey Rye

Last modified: 2017-02-12


We demonstrate an integrated system for building and learning models and structures in both a real and virtual environment. The system combines natural language understanding, planning, and methods for composition of basic concepts into more complicated concepts. The user and the system interact via natural language to jointly plan and execute tasks involving building structures, with clarifications and demonstrations to teach the system along the way. We use the same architecture for building and simulating models of biology, demonstrating the general-purpose nature of the system where domain-specific knowledge is concentrated in sub-modules with the basic interaction remaining domain-independent. These capabilities are supported by our work on semantic parsing, which generates knowledge structures to be grounded in a physical representation, and composed with existing knowledge to create a dynamic plan for completing goals. Prior work on learning from natural language demonstrations enables learning of models from very few demonstrations, and features are extracted from definitions in natural language. We believe this architecture for interaction opens up a wide possibility of human-computer interaction and knowledge transfer through natural language.


natural language processing; dialogue systems; situated agents; planning; biology; learning; symbol grounding; natural language understanding; human-computer interaction

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