UTCS Artificial Intelligence
courses
talks/events
demos
people
projects
publications
software/data
labs
areas
admin
Positioning to Win: A Dynamic Role Assignment and Formation Positioning System (2013)
Patrick MacAlpine
, Francisco Barrera, and
Peter Stone
This paper presents a dynamic role assignment and formation positioning system used by the 2011 RoboCup 3D simulation league champion UT Austin Villa. This positioning system was a key component in allowing the team to win all 24 games it played at the competition during which the team scored 136 goals and conceded none. The positioning system was designed to allow for decentralized coordination among physically realistic simulated humanoid soccer playing robots in the partially observable, non-deterministic, noisy, dynamic, and limited communication setting of the RoboCup 3D simulation league simulator. Although the positioning system is discussed in the context of the RoboCup 3D simulation environment, it is not domain specific and can readily be employed in other RoboCup leagues as it generalizes well to many realistic and real-world multiagent systems.
View:
PDF
,
PS
,
HTML
Citation:
In
{R}obo{C}up-2012: Robot Soccer World Cup {XVI}
2013.
Bibtex:
@incollection{LNAI12-MacAlpine, title={Positioning to Win: A Dynamic Role Assignment and Formation Positioning System}, author={Patrick MacAlpine and Francisco Barrera and Peter Stone}, booktitle={{R}obo{C}up-2012: Robot Soccer World Cup {XVI}}, url="http://www.cs.utexas.edu/users/ai-lab?LNAI12-MacAlpine", year={2013} }
Presentation:
Slides (PDF)
People
Patrick MacAlpine
Ph.D. Student
patmac [at] cs utexas edu
Peter Stone
Faculty
pstone [at] cs utexas edu
Areas of Interest
Humanoid Robots
RoboCup
Simulated Robot Soccer
Labs
Learning Agents