A mechanism represents the actions available to each agent and the (distribution over) outcomes for their joint actions. There are many representations for mechanisms in games, and multiagent interactions in general, that have been proposed in economics and AI. In AI, these representation typically allow the designer to model aspects of games that can be exploited for computational gain.

We present three representations; two of these are classic representations from economics. The first abstracts away all structure of the policies of the agents. The second models the sequential structure of games and is the foundation for much work on representing board games. The third representation moves away from the state-based representation to allow the representation of games in terms of features.