Cooperation and competition are fundamental modes of social interaction. It is imperative that we study such behavior to unravel the staggering complexities of the human brain. We aim to develop a modelling framework to disentangle the neural underpinnings of such behavior with a sophisticated design of the iconic tiger task. The task revolves around the nuances of human decision making where the participant is choosing between two doors hiding a tiger or a gold pot and an option of taking a hint. The task becomes more demanding in the multiplayer setting where one needs to either synchronize actions with the other participant (cooperation) or outsmart the other participant (competition) in order to earn maximum reward. We estimate logistic discrete choice models with Bayesian Hierarchical modeling to model the participants’ choices in the single and multiplayer versions of the task. The inclusion of the social information in the model for the multiplayer version significantly improves the model fit. As an extension to this descriptive model, we will use I-POMDP that explicitly models the other participant as an intentional agent to investigate the theory of mind of cooperation and competition further.