Rich goal types in agent programming

Goals are central to the design and implementation of intelligent software agents. Much of the literature on goals and reasoning about goals in agent programming frameworks only deals with a limited set of goal types, typically achievement goals, and sometimes maintenance goals. In this paper we extend a previously proposed unifying framework for goals with additional richer goal types that are explicitly represented as Linear Temporal Logic (LTL) formulae. We show that these goal types can be modelled as a combination of achieve and maintain goals. This is done by providing an operationalization of these new goal types, and showing that the operationalization generates computation traces that satisfy the temporal formula.