Language Evolution and Computation Bibliography

The paper addresses the question how a group of physically embodied robotic agents may origi- nate meaning and language through adaptive language games. The main principles underlying the approach are sketched as well as the steps needed to implement these principles on physical agents. Some experimen- tal results based on this implementation are presented.

Communication signals in many animal species (including humans) show a surprising amount of variety both across time and at any one instant in a population. Traditional accounts and simulation models of the evolution of communication offer little explanation of this diversity. Sexual selection of signals used to attract mates, and the coevolving preferences used to judge those signals, can instead provide a convincing mechanism. Here we demonstrate that a wide variety of ``songs'' can evolve when male organisms sing their songs to females who judge each male's output and decide whether or not to mate with him based on their own coevolved aesthetics. Evolved variety and rate of innovation are greatest when females combine inherited song preferences with a desire to be surprised. If females choose mates from a small pool of candidates, diversity and rate of change are also increased. Such diversity of communication signals may have implications for the evolution of brains as well.

It is in LSLT, first circulated in 1955, that Chomsky sets out in more detail the theory of generative grammar. In this work "the 'realist' position" is assumed. The theory is "understood as a psychological theory that attempts to characterize the innate human 'language faculty'" (Chomsky ...

Can concepts from the theory of neural computation contribute to formal theories of the mind? Recent research has explored the implications of one principle of neural computation, optimization, for the theory of grammar. Optimization over symbolic linguistic structures provides the core of a new grammatical architecture, optimality theory. The proposition that grammaticality equals optimality sheds light on a wide range of phenomena, from the gulf between production and comprehension in child language, to language learnability, to the fundamental questions of linguistic theory: What is it that the grammars of all languages share, and how may they differ?

The genetic history of a group of populations is usually analyzed by reconstructing a tree of their origins. Reliability of the reconstruction depends on the validity of the hypothesis that genetic differentiation of the populations is mostly due to population fissions followed by independent evolution. If necessary, adjustment for major population admixtures can be made. Dating the fissions requires comparisons with paleoanthropological and paleontological dates, which are few and uncertain. A method of absolute genetic dating recently introduced uses mutation rates as molecular clocks; it was applied to human evolution using microsatellites, which have a sufficiently high mutation rate. Results are comparable with those of other methods and agree with a recent expansion of modern humans from Africa. An alternative method of analysis, useful when there is adequate geographic coverage of regions, is the geographic study of frequencies of alleles or haplotypes. As in the case of trees, it is necessary to summarize data from many loci for conclusions to be acceptable. Results must be independent from the loci used. Multivariate analyses like principal components or multidimensional scaling reveal a number of hidden patterns and evaluate their relative importance. Most patterns found in the analysis of human living populations are likely to be consequences of demographic expansions, determined by technological developments affecting food availability, transportation, or military power. During such expansions, both genes and languages are spread to potentially vast areas. In principle, this tends to create a correlation between the respective evolutionary trees. The correlation is usually positive and often remarkably high. It can be decreased or hidden by phenomena of language replacement and also of gene replacement, usually partial, due to gene flow.

The inference of the evolutionary history of a set of languages is a complex problem. Although some languages are known to be related through descent from common ancestral languages, for other languages determining whether such a relationship holds is itself a difficult problem. In this paper we report on new methods, developed by linguists Johanna Nichols (University of California, Berkeley), Donald Ringe and Ann Taylor (University of Pennsylvania, Philadelphia), and me, for answering some of the most difficult questions in this domain. These methods and the results of the analyses based on these methods were presented in November 1995 at the Symposium on the Frontiers of Science held by the National Academy of Sciences.

The use of biological models and metaphors in studies of culture has a long and checkered history. While there are many superficial similarities between biological and cultural evolution, attempts to pin down such analogies have not been wholly successful. One limiting factor may be a lack of empirical evidence that the basic assumptions of the evolutionary model are met within a cultural system. We argue that a focus on the detection and description of the units of selection is an essential first step in constructing any evolutionary model. In this paper we outline the necessary connection between units of selection and evolution, describe the properties of a unit of selection, and introduce an empirical method for the detection of putative units of selection in a model cultural system: discourse within NetNews, a discussion system on the Internet.

Using a simple model of signaling of fighting ability, I demonstrate that; (1) conventional, cost-free, signals of fighting ability can be an ESS, (2) signals with significant costs can be used at ESS as long as they are used to indicate weakness rather than strength, (3) that if a set of signals is used to indicate a set of fighting abilities through their costs, they must decrease in cost for stronger signalers. The reason for this is that individuals of higher fighting ability have less to gain by avoiding escalated contests, and are thus more sensitive to signal costs. These results are of particular relevance to badges of status and other simultaneous signals used to settle contests over minor resources

There is evidence for increase, followed by decline, in synaptic numbers during development. Dendrites do not function in isolation. A constructive neuronal process may underpin a selectionist cognitive process. The environment shapes both ontogeny and phylogeny. Phylogenetic natural selection and neural selection are compatible. Natural selection can yield both constructivist and selectionist solution to adaptuive problems.

Linguists' intuitions about language change can be captured by a dynamical systems model derived from the dynamics of language acquisition. Rather than having to posit a separate model for diachronic change, as has sometimes been done by drawing on assumptions from population biology (cf. Cavalli-Sforza and Feldman, 1973; 1981; Kroch, 1990), this new model dispenses with these independent assumptions by showing how the behavior of individual language learners leads to emergent, global population characteristics of linguistic communities over several generations. As the simplest case, we formalize the example of two grammars and show that even this situation leads directly to a nonlinear (quadratic) dynamical system. We study this one parameter model in a variety of situations for different kinds of acquisition algorithms and maturational times, showing how different learning theories can have very different evolutionary consequences. This allows us to formulate an evolutionary criterion for the adequacy of grammatical and learning theories. An application of the computational model to the historical loss of Verb Second from Old French to Modern French is described showing how otherwise adequate grammatical theories might fail the evolutionary criterion.

If the members of a population of animals are to enjoy the benefit that might accrue from the exchange of information, their communicative behavior must be coordinated -- most of the time that an animal sends a signal in some type of situation, others respond to the signal in a manner appropriate to the situation that inspired it. We investigate how coordinated communication could emerge among animals capable of producing and responding to simple signals, and how such coordination could be maintained, when new members of a population learn to communicate by observing the other members. We describe a learning procedure that enables an individual to achieve the maximum possible accuracy in communicating with a given population. If all new members of the population use this procedure, or one of the approximations to it we describe, the coordination of the population's communication will steadily increase, ultimately yielding a highly coordinated system. Our results are derived mathematically from a formal model of simple communication systems. We illustrate these results with computational simulations. and discuss their biological plausibility and their relevance to more complex communication systems, including human language.

The aim of the paper is to show that an Artificial Life approach to language tends to change the research agenda on language which has been shared by both the symbolic paradigm and classical connectionism. Artificial Life Neural Networks (ALNNs) are different from classical connectionist networks because they interact with an independent physical environment; are subject to evolutionary, developmental, and cultural change, and not only to learning; and are part of organisms that have a physical body, have a life (are born, develop, and die), and are members of genetic and, sometimes, cultural populations. Using ALNNs to study language shifts the emphasis from research on linguistic forms and laboratory-like tasks to the investigation of the emergence and transmission of language, the use of language, its role in cognition, and language as a populational rather than as an individual phenomenon.

This revolutionary book provides fresh answers to long-standing questions of human origins and consciousness. Drawing on his breakthrough research in comparative neuroscience, Terrence Deacon offers a wealth of insights into the significance of symbolic thinking: from the co-evolutionary exchange between language and brains over two million years of hominid evolution to the ethical repercussions that followed man's newfound access to other people's thoughts and emotions.

Informing these insights is a new understanding of how Darwinian processes underlie the brain's development and function as well as its evolution. In contrast to much contemporary neuroscience that treats the brain as no more or less than a computer, Deacon provides a new clarity of vision into the mechanism of mind. It injects a renewed sense of adventure into the experience of being human.

Bound to become a classic and to stimulate debate and research, The Evolution of Communication looks at species in their natural environments as a way to begin to understand what the real units of analysis of communicating systems are, using arguments about design and function to illuminate both the origin and subsequent evolution of each system. It lights the way for a research program that seriously addresses the problem of how communication systems, including language, have been designed over the course of evolution.

Table of Contents

1 Synopsis of the Argument
2 The Evolution of Communication: Historical Overview
3 Conceptual Issues in the Study of Communication
4 Neurobiological Design and Communication
5 Ontogenetic Design and Communication
6 Adaptive Design and Communication
7 Psychological Design and Communication
8 Comparative Communication: Future Directions

• First book to be written on the major transitions in evolution
• Interdisciplinary, drawing on fields as diverse as molecular biology, linguistics, embryology, and population genetics
• Accessible to anyone with an undergraduate training in the biological sciences
• Written by leading theoretical biologists

During evolution there have been several major changes in the way genetic information is organized and transmitted from one generation to the next. These transitions include the origin of life itself, the first eukaryotic cells, reproduction by sexual means, the appearance of multicellular plants and animals, the emergence of cooperation and of animal societies. This is the first book to discuss all these major transitions and their implications for our understanding of evolution. Clearly written and illustrated with many original diagrams, this book will be welcomed by students and researchers in the fields of evolutionary biology, ecology, and genetics.

TABLE OF CONTENTS
1 Introduction
2 What is Life?
3 Chemical evolution
4 The evolution of templates
5 The chicken and egg problem
6 The origin of translation and the genetic code
7 The origin of protocells
8 The origin of eukaryotes
9 The origin of sex and the nature of species
10 Intragenomic conflict
11 Symbiosis
12 Development in simple organisms
13 Gene regulation and cell heredity
14 The development of spatial patterns
15 Development and evolution
16 The origins of societies
17 The origins of language

This thesis investigates communication between animals with conflicting interests. Particular attention is paid to conventional signalling, in which signals are not inherently costly and information is inferred by convention. This type of signalling is emphasised for two reasons: firstly it is communication in its purest sense, and secondly it seems to more accurately reflect the properties of many biological signals. The costs which maintain the evolutionary stability of communication are of great interest because of the apparent benefit to be gained through the use of misleading signals, such as bluffs. I argue that these stabilising costs emerge from the manner in which receivers respond to signals, rather than being inherent to the signals themselves.

The theoretical papers in this thesis begin with the most basic signalling game and proceed towards a more general understanding of conventional signalling. I begin by investigating the importance of signal cost in the simplest possible model of communication, the Action-Response game. I demonstrate that the signals used do not have to be costly to be reliable, even when the signaller and receiver are in a state of conflict. I then consider the effect of adding costs to signals in a game in which reliable conventional signalling already exists, and demonstrate that the costly signals will be used by the weaker, not stronger, signallers. This demonstrates a stabilising mechanism fundamentally different from that of the handicap hypothesis, with its stabilisation through signal cost. Finally, I identify the conditions other than cost which are necessary for conventional signalling to be evolutionarily stable. These conditions relate to the information which both signaller and receiver must gain over the course of an interaction. Most models used to investigate signalling cannot account for behaviour seen in more complicated biological interactions because they are too simple to produce results other than that of the handicap prediction.

The other work included in this thesis addresses issues raised by the models. I review the literature on threat display use by birds, and present evidence that these displays are conventional signals. The stability of conventional signalling rests upon the existence of some common interest within a larger conflict between signaller and receiver. I present a clear example of communication attributable to common interest between fighting opponents. Cichlids of the species Nannacara anomala use a distinct colour signal, the Medial Line display, to coordinate another agonistic behaviour, tail-beating. It appears that both individuals benefit from the clearer assessment of relative fighting ability that this coordination affords. These N. anomala colour displays are quite conspicuous. It has been assumed that when common interest exists, signals will be very subtle, whereas when signaller and receiver are in conflict, signals will be exaggerated and conspicuous. Using an evolving neural-network model, I demonstrate that selection for exaggerated signals may exist even when the signaller and receiver have complete common interests.

This dissertation identifies the conditions necessary to establish a system of communication in a population of individuals, whether through evolution or learning. A definition of communication is proposed that encompasses the behavior of species ranging from flowers to human beings, and a formal framework for modeling such behavior is presented. Through the use of computational simulations, it is shown that systems of communication evolve in cases where such behavior conveys a selective advantage to both sender and receiver. It is also demonstrated that factors such as kin selection and reciprocal altruism can result in the establishment of communication even when there is no direct pressure on the transmission of signals. In the case of learned communication, it is argued that observational learning is the appropriate learning model. Learning strategies that simply imitate the behavior of others, however, are not suitable. Instead, a learning mechanism must optimize its behavior so as best to communicate with the population it is observing. A Bayesian learning procedure designed to maximize the probability of communicative success is shown to be capable not only of learning an existing communication system, but also constructing such a system from random initial signaling behavior. To examine how animals might actually implement such a procedure, network learning models are considered. It is shown that a simple form of Hebbian learning, well within the grasp of most animals, has the required properties. Given this, it is surprising that learned systems of communication are not more frequent. Evidence from the animal social learning literature suggests that the primary reason for this may be that observational learning is difficult, if not impossible, for non-human animals. Given this, he most basic explanation for why only humans have language may not lie in the ability of learn a complex, syntactic form of communication, but rather in the ability to learn any system of communication at all.