A framework based on evolutionary algorithm for strategy optimization in robot soccer-Reference-Cited by-同舟云学术

A framework based on evolutionary algorithm for strategy optimization in robot soccer

Published:2018-07-12 Issue:16 Volume:23 Page:7287-7302
ISSN:1432-7643
Container-title:Soft Computing
language:en
Short-container-title:Soft Comput

Author:

Larik Asma,Haider Sajjad

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00500-018-3376-6.pdf

Reference27 articles.

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2. Bäck T (1996) Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms. Oxford University Press, Oxford

3. Bezek A (2005) Discovering strategic multi-agent behavior in a robotic soccer domain. In: Proceedings of the fourth international joint conference on autonomous agents and multiagent systems. AAMAS’05. ACM, New York, NY, USA, pp 1177–1178. https://doi.org/10.1145/1082473.1082681

4. Chen S, Lv G, Wang X (2016) Offensive strategy in the 2D soccer simulation league using multi-group ant colony optimization. Int J Adv Robot Syst 13(1):25. https://doi.org/10.5772/62167

5. Cherubini A, Giannone F, Iocchi L (2007) Layered learning for a soccer legged robot helped with a 3D simulator. In: Visser U, Ribeiro F, Ohashi T, Dellaert F (eds) RoboCup 2007: robot soccer world cup XI. Lecture notes in computer science. Springer, Berlin, Heidelberg, pp 385–92. https://doi.org/10.1007/978-3-540-68847-1_39

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