An experimental analysis of Colonel Blotto Games under alternative environments
AbstractIn this paper, we design an experiment based on the Colonel Blotto game with complete information under auction method in which the player allocating more resources to a battlefield wins with certainty. The main contribution of this paper is that we allow the same player to play sequentially under different environments (symmetric and asymmetric resources and different number of battlefields) against computer. Consistent with the theoretical predictions, we find that most of the time players use a ‘complete coverage’ strategy when they have equal or more resources than the opponent and use a ‘guerilla warfare’ strategy when they have fewer resources. We also find that an individual player’s success is relatively high when the player has equal or more resources than the opponent. Finally, we observe that there is an improvement in players’ success both within a treatment and across similar treatments which can be explained by “learning” argument.
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Bibliographic InfoArticle provided by Bilgesel Yayincilik in its journal İktisat İşletme ve Finans.
Volume (Year): 27 (2012)
Issue (Month): 312 ()
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Colonel Blotto Game; Strategic Decision Making; Experimental Design; Panel Data Regression;
Find related papers by JEL classification:
- D03 - Microeconomics - - General - - - Behavioral Microeconomics; Underlying Principles
- C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
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- Cary Deck & Li Hao & David Porter, 2013. "Do Prediction Markets Aid Defenders in a Weak-Link Contest?," Working Papers 13-27, Chapman University, Economic Science Institute.
- Ayala Arad & Ariel Rubinstein, 2012.
"Multi-Dimensional Iterative Reasoning in Action: The Case of the Colonel Blotto Game,"
Levine's Working Paper Archive
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- Arad, Ayala & Rubinstein, Ariel, 2012. "Multi-dimensional iterative reasoning in action: The case of the Colonel Blotto game," Journal of Economic Behavior & Organization, Elsevier, vol. 84(2), pages 571-585.
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