With Chapter Three, we present the concept of efficiency as the driving factor for the evolution of language. We describe the concept of efficiency through the metaphor of tool making. Many other fields also consider efficiency a fundamental feature that drives language evolution: neuro-psychology, neuro-biology, linguistics etc. We give a brief account of their views. So far, our discussion relates language to physical systems in a conversational way. In Chapter four, we turn to a better defined physics idiom to understand in more detail the formal implications of our claim. We explore the definition of a system, the concept of propagation and dispersion, elasticity, and degeneracy and phase transitions, on our way to defining a formally tractable model for the evolution of language. In Chapter Five, we discuss several models that are used in non-traditional ways, especially in the description of language dynamics. We first establish the validity of our approach by comparing how other fields such as biology, neuroscience, artificial intelligence and economics have used similar thinking. We examine how biology uses models of phase transition such as percolation to explain dramatic changes in genetic diversity. Neuroscience uses models that illustrate the behavior of systems on the edge of chaos to explain how we change our mind. This leads to similar kinds of approaches in artificial intelligence. More specifically, the use of the Hopfield model, whose state space is identical to an Ising model: It models the behavior of associative memories. Economics has used Ising models to describe trends in the propagation of information in a market place and to describe structural changes in multi-factor systems. Chapter Six introduces the Ising model, its mathematics, and how we use it. The Ising model has traditionally been used in the illustration of structural changes in material such as from solid to gas. We have modified the Ising model to illustrate more accurately the process of attenuation in language. We use the Ising model to track the dynamics of structural changes between lexical and functional vocabulary. We demonstrate how the dynamics of language evolution can be illustrated using a physical model, to offer a more formally tractable description. Chapter Seven goes beyond Ising to introduce the Darwinian machine of William H. Calvin. His model is akin to the Ising model, though more complex. He proposes a model of the superficial layers of the neocortex and describes the relationships to linguistic and representational concepts. We then introduce our model in the context of Calvin's. We illustrate how the concepts of physics that we have introduced, such as phase transition, can provide additional detail and establish compatibility between our approaches. Since Calvin does not emphasize the notion of phase transition in his model, we propose, in Chapter Eight, ways in which his model can be enhanced. We suggest that a phase transition such as percolation can entrain patterns in an environment that is low in connectivity as a strategy to maximize resources. Chapter Nine concludes with an integration of all the previous ideas that we have described to offer a complete picture of how we can consider all aspects of language in a wholly physical idiom. We hope that this thesis will help answer some of the fundamental questions associated with the study of human language.