Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Complexity in left-associative grammar
Theoretical Computer Science
An introduction to intelligent and autonomous control
An introduction to intelligent and autonomous control
Database semantics for natural language
Artificial Intelligence
Foundations of Computational Linguistics: Man-Machine Communication in Natural Language
Foundations of Computational Linguistics: Man-Machine Communication in Natural Language
A Robust Layered Control System For a Mobile Robot
A Robust Layered Control System For a Mobile Robot
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
A Computational Model of Natural Language Communication: Interpretation, Inference, and Production in Database Semantics
From Word Form Surfaces to Communication
Proceedings of the 2010 conference on Information Modelling and Knowledge Bases XXI
Modeling natural language communication in database semantics
APCCM '09 Proceedings of the Sixth Asia-Pacific Conference on Conceptual Modeling - Volume 96
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As a computational model of natural language communication, Database Semantics For an introduction to DBS see [NLC'06]. For a concise summery see [Hausser 2009a]. (DBS) includes a hearer mode and a speaker mode. For the content to be mapped into language expressions, the speaker mode requires an autonomous control. The control is driven by the overall task of maintaining the agent in a state of balance by connecting the interfaces for recognition with those for action. This paper proposes to realize the principle of balance by sequences of inferences which respond to a deviation from the agent's balance (trigger situation) with a suitable blueprint for action (countermeasure). The control system is evaluated in terms of the agent's relative success in comparison other agents and the absolute success in terms of survival, including the adaptation to new situations (learning). From a software engineering point of view, the central question of an autonomous control is how to structure the content in the agent's memory so that the agent's cognition can precisely select what is relevant and helpful to remedy a current imbalance in real time. Our solution is based on the content-addressable memory of a Word Bank, the data structure of proplets defined as non-recursive feature structures, and the time-linear algorithm of Left-Associative grammar.