Consider the game of poker, and how an emotion model can enhance the believability, and possibly interest, of a computerized version of the game. Using a preliminary model, we have discussed (and built a simple versions of) the following system [Marquis & Elliott1994]:
The computer simulates one, or more, agents who play five card draw poker against the user. Each agent knows the basic rules of poker, including betting. Agents have their own goals, principles, and preferences so that they respond differently to different situations that arise. Bluffing, required if one is to truly simulate poker, leads to fear for some agents, hope for others. Some agents show their emotions (through facial expression, music selection, and verbal communication of physical manifestations), others suppress them (as in real life). An agent who has been bluffing and wins, might gloat, or if it loses it might feel remorse. An increase in the amount of the ``pot'' increases the importance of winning and thus the intensity of many of the emotions. Likewise surprise (generally hard to represent) can be derived from losing even though one has a good hand, or vice versa, thus intensifying the respective emotion. Agents might feel reproach towards, for example, a player (such as the user) who is too cautious, or takes to long to decide what to do (based on a violation of the principled customary way of playing). Other emotion-eliciting situations include having the computer attempt to cheat without being caught by the user, and so forth.
One claim that might be made is that to approach a realistic computer model of games such as poker, some model of personality and emotion, minimally a broad and shallow model as described here, is essential. Whether or not this makes the computer a better playing companion is an open question, but again, one that seems worth answering.