Making meaning happen

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.

Evolutionary Explanations of Indicatives and Imperatives

“…For more on the relationship between animal signals and mentalistic language see Radner (1999). 7 For an analysis of signaling games which include the realistic feature of local interaction see Grim et al (2001) and Zollman (2005). 8 On this view, one may wonder about the status of a cry for help like 'Help!'.…”

Semantic content and pragmatic convention: Emergence through individual advantage in spatialized environments

“…In more recent models, our individuals instantiate simple neural nets, doing a partial training on the behavior of successful neighbors [3], [4].…”

Information-Theoretic Teleodynamics in Natural and Artificial Systems

“…The internal states of the AA are excellent candidates for the role of nonsemantic yet semantic-inducing resources." Indeed, in an earlier study, Grim showed that signs can acquire meanings by coordinating signaling across artificial creatures in an agent-based model [19]. "Truth telling," here, emerged even in elementary models based solely on the interaction between agents, agent-environment relations, and simple mechanisms internal to each agent.…”

“…However, action-based semantics may provide another alternative. (See, for instance, [18] and [19].) Respecting the former, Floridi notes, "in the beginning, the proto-meanings of the symbols generated by an AA [artificial agent] are the internal states of that AA, which in turn are directly correlated to the action performed by the same AA" (p. 164 [18]).…”

“…One is a project in teleodynamic game play in which we will engineer a network to play a formal game using information-theoretic principles and pattern matching rather than heuristic search. The other concerns enriching the communications strategies in Patrick Grim's artificial life model [19], mentioned above, to see if we can build a community of artificial agents that can learn from each other and that might cross the boundary between simple signal processing to something closer to language use. (See the comments from Floridi [18] on action-based semantics above.)…”