Football Simulation implementation with Fuzzy Rule Interpolation-based Fuzzy Automaton

Abstract

This paper introduces the model of a fuzzy automaton controlled football simulation. The controlling of the agents (football players) of the simulation is realized by evaluating such fuzzy rule-bases, which contain only the most important rules able to make the system work (forming so called sparse rule-bases). Classical fuzzy inference methods require complete rule-bases by design and cannot handle this kind of sparse rule-bases. However, by apply-ing fuzzy rule interpolation (FRI), using sparse rule-bases to control the agents becomes possible. The goal of this work is to construct and present such a model, which employs a human-readable knowledge representation to control the football simulation. For this purpose the application of sparse fuzzy rule-bases is well suited, as these are self-describing by their nature.