Abstract
What is it for a sound or gesture to have a meaning, and how does it
come to have one? In this paper, a range of simulations are used to extend the
tradition of theories of meaning as use. The authors work throughout with large
spatialized arrays of sessile individuals in an environment of wandering food sources
and predators. Individuals gain points by feeding and lose points when they are hit
by a predator and are not hiding. They can also make sounds heard by immediate
neighbours in the array, and can respond to sounds from immediate neighbours. No
inherent meaning for these sounds is built into the simulation; under what circumstances they are sent, if any, and what the response to them is, if any, vary initially
with the strategies randomized across the array. These sounds do take on a specific
function for communities of individuals, however, with any of three forms of strategy change: direct imitation of strategies of successful neighbours, a localized genetic
algorithm in which strategies are ‘crossed’ with those of successful neighbours, and
neural net training on the behaviour of successful neighbours. Starting from an array
randomized across a large number of strategies, and using any of these modes of
strategy change, communities of ‘communicators’ emerge. Within these evolving
communities the sounds heard from immediate neighbours, initially arbitrary
across the array, come to be used for very specific communicative functions.
‘Communicators’ make a particular sound on feeding and respond to that same
sound from neighbours by opening their mouths; they make a different sound
when hit with a predator and respond to that sound by hiding. Robustly and persistently, even in simple computer models of communities of self-interested agents,
something suggestively like signalling emerges and spreads.
Keywords: meaning, communication, genetic algorithms, neural networks