A Low Complexity Algorithm for the Least Ambiguous Strategies Selection

D. Stefanoiu, F. Ionescu (Germany), and D. Norrie (Canada)


iterative deepening search, multiagentsystems, planning, fuzzy uncertainty measures.


Artificial Intelligence (AI) is one of the most dynamical research domains, where many non conventional methods for solving optimization problems are continuously developed. And yet, a paradox could be noticed: once a problem has been approached by using AI techniques, the solution seems to leave the AI domain and to join a very specific field of application. In this paper, a method for Multi-Agent Systems (MAS) strategies searching is introduced. The method relies on the Iterative Deepening Algorithm (IDA*) and the fuzzy measure of ambiguity, but it rather belongs to MAS dynamics modeling approaches.

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