@inproceedings{Bee02Agi1,
  author    = "Michael Beetz and Sebastian Buck and Robert Hanek and Thorsten Schmitt and Bernd Radig",
  title     = "The {AGILO} Autonomous Robot Soccer Team: Computational Principles, Experiences, and Perspectives",
  booktitle = "International Joint Conference on Autonomous Agents and Multi Agent Systems (AAMAS) 2002",
  year      = "2002",
  pages     = "805--812",
  address   = "Bologna, Italy",
  bib2html_pubtype  = {Refereed Conference Paper},
  bib2html_rescat   = {Robot Learning, State Estimation, RoboCup},
  bib2html_groups   = {AGILO},
  bib2html_funding  = {AGILO},
  bib2html_keywords = {Learning, Robot, State Estimation, Vision, Reasoning},
  abstract = {This paper describes the computational model underlying the AGILO autonomous robot soccer team, its
              implementation, and our experiences with it. The most salient aspects of the AGILO control software
              are that it includes (1) a cooperative probabilistic game state estimator working with a simple
              off-the-shelf camera system; (2) a situated action selection module that makes amble use of
              experience-based learning and produces coherent team behavior even if inter-robot communication is
              perturbed; and (3) a playbook executor that can perform preprogrammed complex soccer plays in
              appropriate situations by employing plan-based control techniques. The use of such sophisticated
              state estimation and control techniques distinguishes the AGILO software from many others applied
              to mid-size autonomous robot soccer. The paper discusses the computational techniques and necessary
              extensions based on experimental data from the 2001 robot soccer world championship.}
}