Performance, Robustness and Effort Cost Comparison of Machine Learning Mechanisms in FlatLand
Georgios N. Yannakakis, Student Member, John C. T. Hallam, John Hallam, Markos Papageorgiou · University of Southern Denmark Research Portal (University of Southern Denmark) · 2003
This paper presents the first stage of research into a multi-agent complex environment, called "FlatLand" aiming at emerging complex and adaptive obstacle-avoidance and targetachievement behaviors by use of a variety of learning mechanisms. The presentation includes a detailed description of the FlatLand simulated world, the learning mechanisms used as well as an efficient method for comparing the mechanisms' performance, robustness and required computational effort.