Metaheuristic optimization in formal argumentation
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Formal argumentation is an important eld in the development of AI. That is because formal argumentation can draw conclusions form multiple contradictory facts. For this arguments are represented as a graph. The goal of this paper is to develop and implement Simulated Annealing and Tabu Search, two Metaheuristic optimization algorithms for problems faced in formal argumentation. Sets of arguments, called extensions, have to to fulll certain requirements in order to solve these problems. Both algorithms will then be compared to already established algorithms for formal argumentation.
08.10.20 - 10:15
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