"Infographics" team: Selecting Control Parameters via Maximal Fisher Information

“Infographics” is a very new RoboCup Soccer Simulation League 2D team, based on the released source code of agent2d [1] and Gliders [2,3]. It also uses librcsc (a base library for The RoboCup Soccer Simulator, RCSS [4]); soccerwindow2: a viewer program for RCSS; fedit2: a formation editor for agent2d; and GIBBS: in-browser log-player for 2D Simulation League logs [5]. The Soccer Simulation 2D League is one of the oldest RoboCup leagues which still presents a significant challenge for Artificial Intelligence, Machine Learning, Autonomous Agents andMulti-Agent Systems, Cognitive Robotics and Complex Systems [6,7,8,9,10,11,12]. In this paper we describe an approach to utilize Fisher information in interaction networks, produced by dynamics of RoboCup Simulation games. This approach is based on (a) methods for computing interaction networks, introduced in [13] and verified by Gliders [3], and (b) methods for determining Fisher information in complex networks, described in [14]. It guides optimization of control parameters used by “Infographics”.