Abstract—In this study, a bot is developed to compete in the
first International RoShamBo Tournament test suite. The basic
“Beat Frequent Pick (BFP)” algorithm was taken from the
supplied test suite and was improved by adding a random
choice tailored fit against the opponent's distribution of picks. A
training program was also developed that finds the best
performing bot variant by changing the bot's behavior in terms
of the timing of the recomputation of the pick distribution.
Simulation results demonstrate the significantly improved
performance of the proposed variant over the original BFP.
This indicates the potential of using the core technique (of the
proposed variant) as an Artificial Intelligence bot to similarly
applicable computer games.
Index Terms—Artificial intelligence, game theory, rock paper scissors, RoShamBo.
S. E. Valdez is with the Agoo Computer College, Agoo, La Union, Philippines (e-mail: firstname.lastname@example.org).
G. P. Siddayao is with the Cagayan State University-College of Information and Computing Sciences, Tuguegarao City, Philippines 3500 (e-mail: email@example.com).
P. L. Fernandez is with the Ateneo de Manila University, Quezon City, Philippines (e-mail: firstname.lastname@example.org).
Cite: Sony E. Valdez, Generino P. Siddayao, and Proceso L. Fernandez, "The Effectiveness of Using a Modified “Beat Frequent Pick” Algorithm in the First International RoShamBo Tournament," International Journal of Information and Education Technology vol. 5, no. 10, pp. 740-747, 2015.