  We consider a slotted-ALOHA LAN with loss-averse, noncooperative greedy
users. To avoid non-Pareto equilibria, particularly deadlock, we assume
probabilistic loss-averse behavior. This behavior is modeled as a modulated
white noise term, in addition to the greedy term, creating a diffusion process
modeling the game. We observe that when player's modulate with their
throughput, a more efficient exploration of play-space results, and so finding
a Pareto equilibrium is more likely over a given interval of time.
