Abstract: The systems transparency in the field of human-machine interaction and artificial intelligence has seen a growth of interest. Nonetheless, there have been few experimental studies of their effect on teamwork. We analyzed that implicitly through a collaborative game scenario with a mixed human-agent team. During the five rounds of a game, the human player chooses between contributing to the team goal (cooperate) or contributing to his individual goal (defect). We conducted two user studies in Amazon’s Mechanical Turk (MTurk). In the first study we focused on the influence of the agents’ strategy, while in the second study, we manipulated the agents’ transparency. The strategy and the transparency of the agents were examined in a between-subjects design. The analysis regarded the comparison of the cooperative/defect behavior of the player, the perception of the group identification, the trust, the human likeness, the competence and the likeability of the agents for each strategy. The analysis of the data for the entire sample and the filtered sample, based on the participants’ level of understanding of the game, showed some differences. In the first case, there were few statistically significant results, in the second, there were promising results in the interaction effect between the agents’ strategy and transparency.