Abstract
What is the nature of language? How has it evolved in different species? Are there qualitative, well-defined classes of languages? Most studies of language evolution deal in a way or another with such theoretical contraption and explore the outcome of diverse forms of selection on the communication matrix that somewhat optimizes communication. This framework naturally introduces networks mediating the communicating agents, but no systematic analysis of the underlying landscape of possible language graphs has been developed. Here we present a detailed analysis of network properties on a generic model of a communication code, which reveals a rather complex and heterogeneous morphospace of language graphs. Additionally, we use curated data of English words to locate and evaluate real languages within this morphospace. Our findings indicate a surprisingly simple structure in human language unless particles with the ability of naming any other concept are introduced in the vocabulary. These results refine and for the first time complement with empirical data a lasting theoretical tradition around the framework of least effort language.
Highlights
What is the nature of language? How has it evolved in different species? Are there qualitative, welldefined classes of languages? Most studies of language evolution deal in a way or another with such theoretical contraption and explore the outcome of diverse forms of selection on the communication matrix that somewhat optimizes communication
The morphospace has as axes the Multi Objective (or Pareto) Optimization (MOO) target functions
The least-effort model discussed in this paper has long captured the attention of the community. It features a core element of most communication studies – namely, the “coder to noisy-channel to decoder” structure found in Shannon’s original paper on information theory[60], as well as in more recent experiments on the evolution of languages[13,15,16]. This toy model allows us to formulate several questions regarding the optimality of human language and other communication systems
Summary
What is the nature of language? How has it evolved in different species? Are there qualitative, welldefined classes of languages? Most studies of language evolution deal in a way or another with such theoretical contraption and explore the outcome of diverse forms of selection on the communication matrix that somewhat optimizes communication. Despite the obvious complexities and diverse potential strategies to tackle this problem, a common feature is shared by most modelling approximations: an underlying bipartite relationship between signals (words) used to refer to a set of object, concepts, or actions (meanings) that define the external world. Such mapping asumes the existence of speakers and listeners, and is used in models grounded in formal language theory[10], evolutionary game theory[11,12], agent modelling[13,14,15,16,17], and connectionist systems[18]. Such a minimal toy model[20] can be described as a set
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