Alexander, J McKenzie (2013) Learning to signal in a dynamic world. British journal for the philosophy of science . ISSN 0007-0882 (In Press)
Sender-receiver games, first introduced by David Lewis in Convention, have received increased attention in recent years as a formal model for the emergence of communication. Skyrms (2010) showed that simple models of reinforcement learning often succeed in forming efficient, albeit not necessarily minimal, signalling systems for a large family of games. Later, Alexander et al. (2011) showed that reinforcement learning, combined with forgetting, frequently produced both efficient and minimal signalling systems. In this paper I define a dynamic sender-receiver game in which the state-action pairs are not held constant over time, and show that neither of these two models of learning learn to signal in this environment. However, a model of reinforcement learning with discounting of the past does learn to signal; it also gives rise to the phenomenon of linguistic drift.
|Additional Information:||© The Author|
|Library of Congress subject classification:||B Philosophy. Psychology. Religion > B Philosophy (General)|
|Sets:||Departments > Philosophy, Logic and Scientific Method|
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