Peter Stone's Selected Publications

Classified by TopicClassified by Publication TypeSorted by DateSorted by First Author Last NameClassified by Funding Source


UT Austin Villa: RoboCup 2021 3D Simulation League Competition Champions

UT Austin Villa: RoboCup 2021 3D Simulation League Competition Champions.
Patrick MacAlpine, Bo Liu, William Macke, Caroline Wang, and Peter Stone.
In Rachid Alami, Joydeep Biswas, Maya Cakmak, and Oliver Obst, editors, RoboCup 2021: Robot World Cup XXIV, pp. 314–26, Springer International Publishing, 2022.
Accompanying videos at http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2021

Download

[PDF]2.5MB  

Abstract

The UT Austin Villa team, from the University of Texas at Austin, won the 2021 RoboCup 3D Simulation League, winning all 19 games the team played. During the course of the competition the team scored 108 goals while conceding only 5. Additionally the team finished second in the overall RoboCup 3D Simulation League technical challenge by finishing second in both the fat proxy and scientific challenges. This paper details and analyzes the results of the 2021 competition, and also presents a new deep RL learning framework that was presented during the scientific challenge.

BibTeX Entry

@InCollection{LNAI21-MacAlpine,
author="Patrick MacAlpine and Bo Liu and William Macke and Caroline Wang and Peter Stone",
editor="Rachid Alami and Joydeep Biswas and Maya Cakmak and Oliver Obst", 
title="{UT} {A}ustin {V}illa: {R}obo{C}up 2021 3{D} Simulation League Competition Champions",
booktitle="{R}obo{C}up 2021: Robot World Cup {XXIV}",
year="2022",
publisher="Springer International Publishing",
pages="314--26",
abstract="The UT Austin Villa team, from the University of Texas at Austin, won the 2021 RoboCup 3D Simulation League, winning all 19 games the team played. During the course of the competition the team scored 108 goals while conceding only 5. Additionally the team finished second in the overall RoboCup 3D Simulation League technical challenge by finishing second in both the fat proxy and scientific challenges. This paper details and analyzes the results of the 2021 competition, and also presents a new deep RL learning framework that was presented during the scientific challenge.",
  isbn="978-3-030-98682-7",
  wwwnote={Accompanying videos at <a href="http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2021">http://www.cs.utexas.edu/~AustinVilla/sim/3dsimulation/#2021</a>}
}

Generated by bib2html.pl (written by Patrick Riley ) on Mon Mar 25, 2024 00:05:11