Abductive Inference of Plans and Intentions in Information-Seeking Dialogues
A robust man-machine interaction requires the capability for inferring the beliefs and intentions of each active agent. In this article it will be proposed a framework that supports the recognition of plans and intentions through abductive inferences over discourse sentences. The possible actions, world knowledge, events and states are represented by extended logic programs (LP with explicit negation) and the abductive inference process is modeled by the framework proposed by Pereira ([PAA92]) which is based on the Well Founded Semantics augmented with explicit negation (WFSX) and contradiction removal semantics (CRSX). It will be shown how this framework supports abductive planning with Event Calculus ([Esh88]) and some classical examples will be shown ([Lit 85, Pol 86]) in the domain of information-seeking dialogues. Finally, some open problems and future work will be pointed out.
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