"Infographics" team: Selecting Control Parameters via Maximal Fisher Information
Siddharth Pritam
TL;DR
This paper presents a method for selecting control parameters in soccer simulation agents by maximizing Fisher information, aiming to improve agent performance.
Contribution
It introduces a novel approach to parameter selection using maximal Fisher information, enhancing agent tuning in RoboCup simulations.
Findings
Improved agent performance in RoboCup 2014
Effective parameter tuning method demonstrated
Enhanced understanding of control parameter impact
Abstract
Team description paper for RoboCup 2014 Soccer Simulation League 2D.
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Taxonomy
TopicsGaussian Processes and Bayesian Inference · Gene Regulatory Network Analysis · Complex Network Analysis Techniques