Modern interactions with technology have been moving away from simple human use of computers as tools to the establishment of human relationships with autonomous entities that carry out actions on our behalf, thus it is imperative to understand the human-autonomy interaction dynamics for best outcomes. In this project, we develop a two-agent interaction framework in discrete-time that could apply to human-autonomy interaction. We analyze our model and validate it through experimental data. Combined with data, our work is able 13 to investigate team members' characteristics that would drive the team to succeed in a given task. High-performing teams are formed with agents that have constant communication and one agent is acting as a leader. Ideally, the lead agent is coordinating the rest of the team from the outside and therefore their communication is quantitatively higher. The agents' personality and training to complete a task also plays an important role in the quality of the team's communications and therefore their performance in task completion. In addition, our model could potentially help us to select team members that could work together efficiently, and train members in the established team to collaborate better.