Interaction Studies - Volume 10, Issue 1, 2009

It is widely assumed that language in some form or other originated by piggybacking on pre-existing learning mechanism not dedicated to language. Using evolutionary connectionist simulations, we explore the implications of such assumptions by determining the effect of constraints derived from an earlier evolved mechanism for sequential learning on the interaction between biological and linguistic adaptation across generations of language learners. Artificial neural networks were initially allowed to evolve “biologically” to improve their sequential learning abilities, after which language was introduced into the population. We compared the relative contribution of biological and linguistic adaptation by allowing both networks and language to change over time. The simulation results support two main conclusions: First, over generations, a consistent head-ordering emerged due to linguistic adaptation. This is consistent with previous studies suggesting that some apparently arbitrary aspects of linguistic structure may arise from cognitive constraints on sequential learning. Second, when networks were selected to maintain a good level of performance on the sequential learning task, language learnability is significantly improved by linguistic adaptation but not by biological adaptation. Indeed, the pressure toward maintaining a high level of sequential learning performance prevented biological assimilation of linguistic-specific knowledge from occurring.

In this paper, we propose two agent-based simulation models for the evolution of language in the framework of evolutionary language games. The theory of evolutionary language games arose from the union of evolutionary game theory, introduced by the English biologist John Maynard Smith, and language games, developed by the Austrian philosopher Ludwig Wittgenstein. The first model proposed is based on Martin Nowak’s work and is designed to reproduce and verify (or refute) the results Nowak obtained in his simplest mathematical model. For the second model, we extend the previous one with the introduction of a world where the languages live and evolve, and which influences interactions among individuals. The main goal of this research is to present a model which shows how the presence of a topological structure influences the communication among individuals and contributes to the emergence of clusters of different languages.

The majority of the extant languages have one of three dominant basic word orders: SVO, SOV or VSO. Various hypotheses have been proposed to explain this word order bias, including the existence of a universal grammar, the learnability imposed by cognitive constraints, the descent of modern languages from an ancestral protolanguage, and the constraints from functional principles. We run simulations using a multi-agent computational model to study this bias. Following a local order approach, the model simulates individual language processing mechanisms in production and comprehension. The simulation results demonstrate that the semantic structures that a language encodes can constrain the global syntax, and that local syntax can help trigger bias towards the global order SOV/SVO (or VOS/OVS).

Social learning is a source of behaviour for many species, but few use it as extensively as they seemingly could. In this article, I attempt to clarify our understanding of why this might be. I discuss the potential computational properties of social learning, then examine the phenomenon in nature through creating a taxonomy of the representations that might underly it. This is achieved by first producing a simplified taxonomy of the established forms of social learning, then describing the primitive capacities necessary to support them, and finally considering which of these capacities we actually have evidence for. I then discuss theoretical limits on cultural evolution, which include having sufficient information transmitted to support robust representations capable of supporting variation for evolution, and the need for limiting the extent of social conformity to avoid ecological fragility. Finally, I show how these arguments can inform several key scientific questions, including the uniqueness of human culture, the long lifespans of cultural species, and the propensity of animals to seemingly have knowledge about a phenomenon well before they will act upon it.