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CMU-CS-01-165
Computer Science Department
School of Computer Science, Carnegie Mellon University
CMU-CS-01-165
Selecting Heterogeneous Team Players by Case-Based Reasoning:
A Case Study in Robotic Soccer Simulation
Thomas Gabel*, Manuela Veloso
December 2001
CMU-CS-01-165.ps
CMU-CS-01-165.pdf
Keywords: Robotic soccer simulation, coach, heterogeneous
players, case-based reasoning, genetic algorithms
It is a vital behaviour pattern of humans, the most highly developed
autonomous agents, to make use of experiences accumulated in the past
and to solve new problems in analogy to solutions of old, yet similar
problems. This report gives an outline of our work to apply that
case-based approach to an artificial agent in the domain of Robotic
Soccer simulation. We enable the online coach of a robotic soccer team
to determine the team line-up by a technique that incorporates knowledge
into its reasoning process that was gained from former soccer matches.
In order to use the knowledge contained in old cases, it is
indispensable to define a meaningful evaluation of old solutions. Moreover,
it is necessary to retrieve and adapt those solutions whose application
to the current problem situation promises to be most auspicious. For
these reasons, we also concentrate on the assessment of a team's
performance. Further, we focus on a most precise calculation of the
similarity between heterogeneous player types.
49 pages
*Performed while a visitor at Carnegie Mellon from the University of
Kaiserslautern, Germany.
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