Cyrus 2D Simulation Team Description Paper2018
This work addresses behavior prediction for multi-agent systems in soccer simulation, but it appears incremental as it builds on existing base code and datasets.
The paper tackles predicting player behavior in multi-agent soccer simulations using a neural network trained on three-level datasets from past RoboCup matches, with results applied to block, mark, and defensive decisions.
Cyrus 2D Soccer Simulation was established 2012 with the aim of research and develop in multi agents systems. This year we have joined with Ziziphus for collaboration and speed up our researches. This paper express a brief description of a method for predicting player's behavior in a multi agent system using neural network with a dataset in three level (low, mid, high). The dataset was obtained from log files of past years RoboCup's matches. Behavior Prediction is used in block, mark and defensive decisions. The base code that Cyrus used is agent 3.11.