Abstract
We introduce a special family of (assumption-based argumentation) frameworks for reasoning about the benefits of decisions. These frameworks can be used for representing the knowledge of intelligent agents that can autonomously choose the “best” decisions, given subjective needs and preferences of decision-makers they “represent”. We understand “best” decisions as dominant ones, giving more benefits than any other decisions. Dominant decisions correspond, within the family of argumentation frameworks considered, to admissible arguments. We also propose the use of degrees of admissibility of arguments as a heuristic to assess subjectively the value of decisions and rank them from “best” (dominant) to “worst”. We extend this method to provide notion of relative value of decisions where preferences over benefits are taken into account. Finally, we show how our techniques can be successfully applied to the problem of selecting satellite images to monitor oil spills, to support electronic marketplaces for earth observation products.
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Matt, PA., Toni, F., Vaccari, J.R. (2010). Dominant Decisions by Argumentation Agents. In: McBurney, P., Rahwan, I., Parsons, S., Maudet, N. (eds) Argumentation in Multi-Agent Systems. ArgMAS 2009. Lecture Notes in Computer Science(), vol 6057. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12805-9_3
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DOI: https://doi.org/10.1007/978-3-642-12805-9_3
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