| Reliable flow of communications is essential in today’s operations where the War Fighter depends on the timely dissemination of information. While communications and networking technologies have increased the capacities of military networks, demand is growing faster than capability. When faced with bandwidth limitations, users tend to modify their usage on a network to maximize their benefit given limited resources. For example if a user has access to a number of different types of communication means such as text, voice or video, the use of each of those means results in a different mission payoffs. By balancing these means the user will attempt to maximize their overall mission payoff. Taking into account the fact that the payoff will depend on the network performance differently for each one of these options (e.g. text messaging can tolerate higher network delays than video), we end up with a complex behavior paradigm where users continuously are trying to maximize their payoff while their actions affect the network load and therefore their payoff as well as the payoffs of others. We attempt to model human behavior in a complex fixed network using Game Theoretic techniques. We present the "game" as users playing against the network. We further define how soldiers (players) make choices (strategies) depending on their benefits (payoffs) as well as converging to possible outcomes (Nash Equilibria) associated with various types of games. We assume that players can deduce a sufficient amount of information from their interactions with the network in order to make decisions dynamically and rationally to affect the future payoffs they receive. We will setup the framework for exploring these dynamic learning games and define the relationships between the different elements of these games. Finally, we will present simulation results calculating game outcomes that can be used to estimate how users would utilize a bandwidth restricted network. |