Syntactic Possibilistic Goal Generation
Abstract
We propose syntactic deliberation and goal election al-gorithms for possibilistic agents which are able to deal with incom-plete and imprecise information in a dynamic world. We show that the proposed algorithms are equivalent to their semantic counterparts already presented in the literature. We show that they lead to an ef-ficient implementation of a possibilistic BDI model of agency which integrates goal generation.
Domains
Artificial Intelligence [cs.AI]
Origin : Files produced by the author(s)
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