Fuzzy Mediation as a Dynamic Extension to Information Fusion

Abstract

This paper presents an innovative approach to the field of information fusion. Fuzzy mediation differentiates itself from other algorithms, as this approach is dynamic in nature. The experiments reported in this work analyze the interaction of two distinct controllers as they try to maneuver an artificial agent through a path. Fuzzy mediation functions as fusion engine to integrate the two inputs to produce a single output. Results show that fuzzy mediation is a valid method to mediate between two distinct controllers. The work reported in this article lays the foundation for the creation of an effective tool that uses positive feedback systems instead of negative ones to train human and non-human agents in the performance of control tasks.