neural networks research group
Keepaway player framework source code, version 0.6
The Keepaway player framework is an implementation of all the low- and mid-level keepaway behaviors described in the publications above. The intended purpose of this code is to allow other researchers to compare different machine learning techniques on a common benchmark platform. More details about the framework, along with current benchmark results, can be found in the following paper:
Keepaway Soccer: From Machine Learning Testbed to Benchmark
Peter Stone, Gregory Kuhlmann, Matthew E. Taylor, and Yaxin Liu.
In RoboCup-2005: Robot Soccer World Cup IX, Springer Verlag, Berlin, 2006.
This code is provided "as is" as a resource to the community. All implied or expressed warranties are disclaimed. However, we welcome feedback regarding if and how you were able to use it. Also, we are interested in hearing your ideas about how it can be improved. This code has only been tested on Debian Linux 3.1.
pstone [at] cs utexas edu
Simulated RoboCup Soccer
Areas of Interest