๐ Abstract: This paper is going to represent the output and implemented methods of ARAS 2D Soccer Simulation Team. These approaches are categorized in offense strategies and defense strategies. For each part we have applied different algorithms due to the problem and the chosen solution. These algorithms are varied in machine learning, matching and plate division algorithms.
โ๏ธ Authors: Fan Wang, YuTang Guo, XingQi Zheng and XinYu Liu
๐ Abstract: This team description paper mainly explains the work of Alice2D at this stage.According to the characteristics of our team, based on the past research, our team is committed to studying the differences of players' roles and reinforcement learning algorithm,changes to the evaluator,formation optimization. After many tests, we continuously optimize the team code, which has greatly improved the performance of the court.
๐ Abstract: This paper describes Austras2D latest team activities and strategies for improving the starter-stack base, published by Nader Zare[1]. We will describe our offence strategies such as decision tree, our shoot, pass and unmarking, as well as defense strategies such as ball block, Intersection-marking and shoot block. At the conclusion, the result of changes we made will be compared with the base version.
๐ Title: CYRUS Soccer Simulation 2D Team DescriptionPaper 2021
โ๏ธ Authors: Nader Zare, Aref Sayareh, Mahtab Sarvmaili, Omid Amini, Amยดฤฑlca Soares, and Stan Matwin
๐ Abstract: In this report, we briefly present the technical procedure and simulation steps for the 2D soccer simulation of team Cyrus. We emphasize on this document on how the prediction of teammatesโ behavior is performed. In our proposed method, the agent receives the noisy inputs from the server, and predicts the ball holder full state behavior. Taking advantage of this approach for choosing the optimal view angle shows 11.30% improvement on the expected win rate.
โ๏ธ Authors: Thomas Gabel, Philipp Klยจoppner, Yalcin Eren, Fabian Sommer, Steffen Breuer, Eicke Godehardt
๐ Abstract: The main focus of FRA-UNItedโs effort in the RoboCup soccer simulation 2D domain is to develop and to apply machine learning techniques in complex domains. In particular, we are interested in applying reinforcement learning methods, where the training signal is only given in terms of success or failure. In this paper, we review some of our recent efforts1 putting a special focus on a new Python-based framework for performing reinforcement learning experiments in the context of 2D soccer simulation.
๐ Abstract: This team description paper introduces the overview of the previous works and the recent research themes of Team HELIOS2021. We have been working on the improvement of statistical team performance indicators (e.g., winning rate and the average of scored goals) by considering the difference in the abilities between our and opponentโs player agents. We propose a method that takes such ability-difference into account to swap the positions within our team. We also present an team evaluation system which has a client server architecture, which automatically perform a lot of games and analyze the game results through the interaction with a human operator. This team evaluation system can also be extended to develop an online competition manager.
๐ Title: Hades2D soccer2D simulation Team Description paper
โ๏ธ Authors: Fatemeh Akhondi, Sama Esmaelifar, Sana Esmaelifar, Seyedeh Raha Rokni, Adrina Rajabi, and Ghazal Hasanpour
๐ Abstract: This article contains descriptions of the activities of the Hades2D soccer 2D simulation team. This year, our team tried to increase the accuracy of both defense and offense strategies. So we developed our ideas by designing and developing algorithms. Here are some of these algorithms and solutions.
โ๏ธ Authors: Wang junyang, Cao Mingkuan, Wang Hao and Fang Baofu
๐ Abstract: This paper mainly describes the related work of HfutEngine2D in 2019-2021, including the optimization of running mode, the optimization of passing and the application of logistic regression model. Combined with the characteristics of HfutEngine2D, this paper expounds the algorithm concept, design intention, application process and progress in detail. In our recent test with other RoboCup strong teams, the strength of HfutEngine2D team has been significantly improved, and for the longterm development of the team, these improvements have also played a great benefit.
๐ Title: ITAndroids 2D Soccer Simulation Team Description Paper 2021
โ๏ธ Authors: Diego T. M. Fidalgo, Felipe V. Coimbra, Gustavo F. Gottschild, Jony dos S. S. Filho, Vinicius F. Almeida, and Marcos R. O. A. Maximo
๐ Abstract: ITAndroids 2D Soccer Simulation team is composed by undergraduate students of Aeronautics Institute of Technology. The team is currently one of the strongest teams in Brazil, having won 1st place 4 times consecutively from 2012 to 2015, Vice Champion in 2018 and was the Champion in 2019 Latin American Competition. Moreover, the team has qualified for the last seven editions of RoboCup, having participated of five. This paper describes some of our advances in 2019 and our plans for 2020.
๐ Abstract: This team description paper introduces the resent research theme of the team Jyo_sen2021. The team is now working on the analysis of soccer formations. We investigate which soccer formation is more efficient than the others, by comparing formations used by professional soccer teams and those used at ancient battle fields in Samurai-era. In addition, we develop an automated test program called cszp for efficient analysis
๐ Abstract: MT2021 is a team of 2D soccer simulation league which is consisted of the students who are coming from Hefei University and all of them are with strong robot enthusiasm. Since 2012, the MT2021 team has participated in RoboCup China open tournament, since 2015, our team has participated in RoboCup World Cup every year and has achieved many good results. This paper briefly describes the background of MT2021 and the main works of our team since the 2019 RoboCup World Cup. Through these works we have greatly improved the competive ability of our team.
โ๏ธ Authors: Sebastian Marian, Dorin Luca, Bogdan Sarac, Ovidiu Cotarlea
๐ Abstract: Oxsy team was founded in July 2002 for a graduation project of one student, Sebastian Marian, in the field of Multi-Agent Systems [1], at the Department of Computer Science of Lucian Blaga University (Sibiu - Romania). After graduation he continued the work on this project and so was born Oxsy team. As we started from scratch, our ideas, concepts and beliefs, was implemented year by year and today, we are happy to see that we are on the right way, as our team was growing in these years, more than we expected from the beginning. If we will qualify to the competition, this year weโll reach at the 17h participation, in RoboCup [4] Soccer Simulation League.
๐ Abstract: This paper includes some explanations about algorithms implemented by Persepolis team members. We will introduce algorithms that are used for pass, shoot, dribbling and marking, and in particular with the ranking algorithm for the states of chain action. The base code used by Persepolis is agent-2d 3.1.1[17].
โ๏ธ Authors: Cristiano Santos de Oliveira, Mateus Gonยธcalves Machado, Walber de Macedo Rodrigues, Thiago da Silva Araยดujo, Pedro Vitor Cunha1, Rafael dos Reis de Labio, Felipe Nunes de Almeida Pereira Mateus Ferreira Borges Soares,Edna Natividade da Silva Barros, Tsang Ing Ren, and Paulo Salgado Gomes de Mattos Neto
๐ Abstract: RobหoCIn Soccer Simulation 2D team started in 2018 at the Universidade Federal de Pernambuco. Our first competition was at Joหao Pessoa, Paraยดฤฑba, Brazil in Latin American Robotics Competition (LARC) 2018 where we obtained the 4th place against teams from Latin America. In 2019 we participated for the first time at the RoboCup, obtained the 9th place and we also participated at the Brazil RoboCup Open 2019 (LARC) where we obtained the 2nd place. In 2020 we participated at the Brazil RoboCup Open 2020 (LARC) where we obtained the 3rd place. In this paper we describe the evolution of the approaches developed last year, the new improvements and researches we made for the simulation 2D.
๐ Title: ThunderLeague: Team Description Paper 2021
โ๏ธ Authors: Caio de Souza Barbosa Costa, Giovanni Cabral Morales, Antonio Lago Araยดujo Seixas, Gabriel Cosme, Lucas Pavan, Maria Fernanda Fernandes Rezende, and Ricardo Tamay Honda
๐ Abstract: The ThundeRatz robotics team has created a RoboCup 2D Soccer Simulation team in 2018 and has been improving since then. This paper brings what we developed until now that made us achieve the position of one of the main 2D Soccer teams in Brazil. Most of the advances described here were inspired in the Gliders2D source code, that are: the pressing and blocking behavior, the evaluator algorithm for defensive and attack purposes and the implementation of better playerโs positioning behaviour. Besides that, we also modified and created new formations using the Fedit2 editor. All those changes combined allowed the team to achieve better defensive results in comparison with Gliders2D v1.5.
๐ Abstract: YuShan Soccer 2D Simulation Team was established in 2009, affiliated with AnHui University of Technology in China. Having participated in RoboCup six times since 2012, YuShan team ranked 4th in the RoboCup2019 in Sydney, Australia and won three consecutive championships in RoboCup China Open Tournaments from 2016 to 2018.In recent years, YuShan team has used data mining technology to analyze the characteristics of the team, and on this basis, proposed a digital twin framework. In the formation, player movement, passing analysis, shooting strategy, offensive and defensive judgment as well as other aspects have achieved some results. The development of YuShan 2020 is depended on YuShan base, and YuShan base is based on the reconstruction project of agent-2d3.1.0 [1], mainly including attack module and defense module.