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In the framework of computational cognitive modeling, natural language understanding and generation must be integrated with other cognitive capabilities, such as reasoning and learning. The language understanding component of an intelligent agent extracts and formally represents the meaning of texts and dialog turns. The output of language understanding must reflect the speaker’s intended meaning and be sufficiently detailed to serve as input to reasoning and action in artificial intelligent agents. One kind of agent action is verbal, so agents must include a language generation capability. This chapter describes a particular language understanding system that meets the requirements for the above language capabilities and also puts forward methodological arguments about the interplay between theories, models, and computational systems.
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