We distinguish three main, overlapping activities in an advice-giving dialogue: problem formulation, resolution, and explanation. This paper focuses on a problem formulation activity in a dialogue module which interacts on one side with an expert problem solver for financial investing and on the other side with a natural language front-end. Several strategies which reflect specific aspects of person-machine advice-giving dialogues are realized by incorporating planning at a high-level of dialogue.
In this paper we present the implementation of an advice-giving system for financial investment for the final phase of the project ESTEAM-3 161. This system integrates multiple agents in a single architecture allowing cooperation between a natural language dialoguer, "~ltelligent" data base access modules, and a problem solver in the financial domain. Using a user model, this system adapts the mixed initiative dialogue during both the formulation of the problem and its resolution by the expert. A novice user thus has access to expert knowledge despite the weakness of his own knowledge.
In this paper we present the implementation of an advice-giving system for financial investment for the final phase of the project ESTEAM-3 161. This system integrates multiple agents in a single architecture allowing cooperation between a natural language dialoguer, "~ltelligent" data base access modules, and a problem solver in the financial domain. Using a user model, this system adapts the mixed initiative dialogue during both the formulation of the problem and its resolution by the expert. A novice user thus has access to expert knowledge despite the weakness of his own knowledge.
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