An Intelligent Man-Machine Dialogue System Based on AI Planning |
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Authors: | Bart Kuijpers Kris Dockx |
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Affiliation: | (1) Department of Mathematics and Computer Science, University of Antwerp (UIA), Universiteitsplein 1, B-2610 Antwerpen;(2) Department of Chemical Engineering, Katholieke Universiteit Leuven, de Croylaan 46, B-3001 Leuven |
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Abstract: | We describe the modular architecture of a generic dialogue system that assists a user/operator in performing a task with a tool. This coaching system is named CALLIOPE after the Greek goddess of eloquence. It aims at being an active partner in an intelligent man-machine dialogue. The intelligent dimension of the coaching system is reflected by its ability to adapt to the user and the situation at hand. The CALLIOPE system contains an explicit user model and world model to situate its dialogue actions. A plan library allows it to follow loosely predetermined dialogue scenarios.The heart of the coaching system is an AI planning module, which plans a series of dialogue actions. We present a coherent set of three dialogue or speech actions that will make up the physical form of the man-machine communication.The use of the AI planning paradigm as a basis for man-machine interaction is motivated by research in various disciplines, as e.g., AI, Cognitive Science and Social Sciences. Starting from the man-man communication metaphor, we can view the thinking before speaking of a human communication partner as constructing an underlying plan which is responsible for the purposiveness, the organisation and the relevance of the communication.CALLIOPE has been fully implemented and tested on theoretical examples. At present, also three tailored versions of CALLIOPE are in operational use in different industrial application domains: operator support for remedying tasks in chemical process industry, operator support for a combined task of planning, plan execution and process control in the area of chemical process development, and thirdly decision support in production scheduling. |
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Keywords: | man-machine interaction dialogue planning AI planning scenarios |
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