Abstract
Classical goal-based reasoning frameworks for agents suppose goals are either achieved fully or not achieved at all: unless achieved completely, the agents have failed to address them. This behavior is different from how people do and therefore is far from real-world scenarios: in every moment a goal has reached a certain level of satisfaction.
This work proposes to extend the classical boolean definition of goal achievement by adopting a novel approach, the Distance to Goal Satisfaction, a metric to measure the distance to the full satisfaction of a logic formula.
In this paper we defined and implemented this metric; subsequently, we extended MUSA, a self-adaptive middleware used to engineer a heterogeneous range of applications. This extension allows solving real situations in which the full achievement represented a limitation.
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Cossentino, M., Sabatucci, L., Lopes, S. (2019). Partial and Full Goal Satisfaction in the MUSA Middleware. In: Slavkovik, M. (eds) Multi-Agent Systems. EUMAS 2018. Lecture Notes in Computer Science(), vol 11450. Springer, Cham. https://doi.org/10.1007/978-3-030-14174-5_2
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