A Low Complexity Algorithm for the Least Ambiguous Strategies Selection

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


iterative deepening search, multi-agentsystems, 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.

Important Links:

Go Back