One of the challenges in modeling human behavior is accurately capturing the conditions under which people will behave selfishly or selflessly. Researchers have been unable to craft purely cooperative (or competitive) scenarios without significant numbers of subjects displaying unintended selfish (or selfless) behavior (e.g., Rapoport & Chammah, 1965). In this work, rather than try to further isolate competitive vs. cooperative behavior, we instead construct an experimental setting that deliberately includes both, in a way that fits within an operational simulation model. Using PsychSim, a multiagent social simulation framework with both Theory of Mind and decision theory, we have implemented an online resource allocation game called “Team of Rivalsâ€�, where four players seek to defeat a common enemy. The players have individual pools of resources which they can allocate toward that common goal. In addition to their progress toward this common goal, the players also receive individual feedback, in terms of the number of resources they own and have won from the enemy. By giving the players both an explicit cooperative goal and implicit feedback on potential competitive goals, we give them room to behave anywhere on the spectrum between these two extremes. Furthermore, by moving away from the more common two-player laboratory settings (e.g., Prisoner's Dilemma), we can observe differential behavior across the richer space of possible interpersonal relationships. We discuss the design of the game that allows us to observe and analyze these relationships from human behavior data acquired through this game. We then describe decision-theoretic agents that can simulate hypothesized variations on human behavior. Finally, we present results of a preliminary playtest of the testbed and discuss the gathered data.