Recognizing formations in opponent teams

Ubbo E Visser, Christian Drücker, Sebastian Hübner, Esko Schmidt, Hans Georg Weland

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)

Abstract

The online coach within the simulation league has become more powerful over the last few years. Therefore, new options with regard to the recognition of the opponents strategy are possible. For example, the online coach is the only player who gets the information of all the objects on the field. This leads to the idea determine the opponents play system by the online coach and then choose an effective counter-strategy. This has been done with the help of an artificial neural network and will be discussed in this paper. All soccer-clients are initialized with a specific behavior and can change their behavior to an appropriate mode depending on the coach's commands. The result is a flexible and effective game played by the eleven soccer-clients.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages391-396
Number of pages6
Volume2019 LNAI
StatePublished - 2001
Externally publishedYes
Event4th Robot World Cup Soccer Games and Conferences, RoboCup 2000 - Melbourne, VIC, Australia
Duration: Aug 27 2000Sep 3 2000

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2019 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th Robot World Cup Soccer Games and Conferences, RoboCup 2000
CountryAustralia
CityMelbourne, VIC
Period8/27/009/3/00

Fingerprint

Neural networks
Artificial Neural Network
Choose
Game
Simulation
Strategy
Object

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Visser, U. E., Drücker, C., Hübner, S., Schmidt, E., & Weland, H. G. (2001). Recognizing formations in opponent teams. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2019 LNAI, pp. 391-396). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2019 LNAI).

Recognizing formations in opponent teams. / Visser, Ubbo E; Drücker, Christian; Hübner, Sebastian; Schmidt, Esko; Weland, Hans Georg.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2019 LNAI 2001. p. 391-396 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2019 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Visser, UE, Drücker, C, Hübner, S, Schmidt, E & Weland, HG 2001, Recognizing formations in opponent teams. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 2019 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2019 LNAI, pp. 391-396, 4th Robot World Cup Soccer Games and Conferences, RoboCup 2000, Melbourne, VIC, Australia, 8/27/00.
Visser UE, Drücker C, Hübner S, Schmidt E, Weland HG. Recognizing formations in opponent teams. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2019 LNAI. 2001. p. 391-396. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Visser, Ubbo E ; Drücker, Christian ; Hübner, Sebastian ; Schmidt, Esko ; Weland, Hans Georg. / Recognizing formations in opponent teams. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2019 LNAI 2001. pp. 391-396 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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