Laziness as a communicative virtue: evolutionary game theory and ambiguous signals
In this research I use game-theoretic analysis and individual-based simulations to suggest that communication is often imprecise because ambiguity can be more efficient than clarity. By treating communication as a problem in coordination, evolutionary game theorists have demonstrated how natural selection leads to signal users being understood by other members of their species. Given the ability to make a variety of signals, populations in game-theoretic models will evolve towards using each of those signals to represent a state of the world. In these models, however, the communication systems that emerge are a little too neat: under the most realistic dynamics, simulated populations end up using perfectly precise signaling systems. This is unlike the real world, where communication is almost always imprecise. Theorists have explained this discrepancy between the models and the real world by arguing that imprecision comes from limited intelligence or conflict between communicators. While I accept these as partial explanations of why communication is messy, it seems to me that communication is often ambiguous merely because signal senders can get away with being imprecise without hurting their cooperative aims. To validate this intuition I show how a simple adjustment to classic signaling games can favor the evolution of ambiguity in simulated populations. I add two elements to the model: a cost for more complex signaling strategies, and the ability to combine information in signals with independent information. Analysis and simulation of the altered model shows that it leads to the predicted outcome of evolution favoring ambiguous signaling.