On the Modeling and Agent-Based Simulation of a Cooperative Group Anagram Game

Madhav Marathe, Naren Ramakrishnan, Parang Saraf, Nathan Self, Abhijin Adiga, Gizem Korkmaz, Chris Kuhlman

Abstract

Anagram games (i.e., word construction games in which players use letters to form words) have been researched for some 60 years. Games with individual players are the subject of over 20 published investigations. Moreover, there are many popular commercial anagram games such as Scrabble. Recently, cooperative team play of anagram games has been studied experimentally. With all of the experimental work and the popularity of such games, it is somewhat surprising that very little modeling of anagram games has been done to predict player behavior/actions in them. We devise a cooperative group anagram game and develop an agent-based modeling and simulation framework to capture player interactions of sharing letters and forming words. Our primary goals are to understand, quantitatively predict, and explain individual and aggregate group behavior, through simulations, to inform the design of a group anagram game experimental platform.

Zhihao Hu, Dustin Machi, Madhav V. Marathe, S. S. Ravi, Yihui Ren, Vanessa Cedeno-Mieles , Saliya Ekanayake, Xinwei Deng, Brian J. Goode, Naren Ramakrishnan, Parang Saraf, Nathan Self, Abhijin Adiga, Gizem Korkmaz, Chris J. Kuhlman:
On the Modeling and Agent-Based Simulation of a Cooperative Group Anagram Game. WSC 2019: 169-180