We propose syntactic deliberation and goal election algorithms for possibilistic agents which are able to deal with incomplete 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 efficient implementation of a possibilistic BDI model of agency which integrates goal generation.
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