@InProceedings{Bee02Agi2,
  author    = "Michael Beetz and Sebastian Buck and Robert Hanek and Andreas Hofhauser and Thorsten Schmitt",
  title     = "{AGILO RoboCuppers 2002: Applying Cooperative Game State Estimation Experience-based Learning, and Plan-based Control to Autonomous Robot Soccer}",
  booktitle = "RoboCup International Symposium 2002",
  series    = "Lecture Notes in Computer Science",
  year      = "2002",
  bib2html_pubtype  = {Refereed Conference Paper},
  bib2html_rescat   = {RoboCup, State Estimation, Robot Vision, Robot Learning, Plan-based Robot Control},
  bib2html_groups   = {AGILO},
  bib2html_funding  = {AGILO},
  bib2html_keywords = {Robot, Planning, Learning, State Estimation, Vision},
  abstract = {This paper describes the computational model underlying the AGILO autonomous robot soccer team and
              its implementation. 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 characterizes the AGILO software. The paper discusses the computational techniques and
              necessary extensions based on experimental data from the 2001 robot soccer world championship.}
}