Language Evolution and Computation Bibliography

This paper reports on the current state of our efforts to shed light on the origin and evolution of linguistic diversity by using synthetic modeling and artificial life techniques. We construct a simple abstract model of a communication system that has been designed with regard to referential signaling in nonhuman animals. The evolutionary dynamics of vocabulary sharing is analyzed based on these experiments. The results show that mutation rates, population size, and resource restrictions define the classes of vocabulary sharing. We also see a dynamic equilibrium, where two states, a state with one dominant shared word and a state with several dominant shared words, take turns appearing. We incorporate the idea of the abstract model into a more concrete situation and present an agent-based model to verify the results of the abstract model and to examine the possibility of using linguistic diversity in the field of distributed AI and robotics. It has been shown that the evolution of linguistic diversity in vocabulary sharing will support cooperative behavior in a population of agents.

If human behavior were list-like, accounting for human behavior would be simple: Just enumerate the list of possible stereotypies. Alternatively, if behavior were predictable on the basis of abstract, fully-productive, context-insensitive rules, our task would be different but ...

In this paper we present an approach to modeling emergent syllable systems using simulated evolution of a ``vocabulary'' of ``words.'' The model is aimed at testing the general hypothesis that language-universal sound patterns emerge from selection pressures exerted on the system by the perceptual and articulatory constraints of language users. The model is able to distinguish between hypotheses about how specific, biologicallymotivated constraints affect the sound structure of language. For example, it is shown that mandibular oscillation provides a strong constraint on the sequential organization of phonemes into words. Future work will explore the potential of other constraints that, with mandibular oscillation, will be sufficient to describe the emergence of syllable systems.

We describe a Genetic Algorithm that can evolve complete programs. Using a variable length linear genome to govern how a Backus Naur Form grammar definition is mapped to a program, expressions and programs of arbitrary complexity may be evolved. Other automatic programming methods are described, before our system, Grammatical Evolution, is applied to a symbolic regression problem.

We develop a new framework for studying the biases that recurrent neural networks bring to language processing tasks. A semantic concept represented by a point in Euclidian space is translated into a symbol sequence by an encoder network. This sequence is then fed to a decoder network which attempts to translate it back to the original concept. We show how a pair of recurrent networks acting as encoder and decoder can develop their own symbolic language that is serially transmitted between them either forwards or backwards. The encoder and decoder bring different constraints to the task, and these early results indicate that the conflicting nature of these constraints may be reflected in the language that ultimately emerges, providing important clues to the structure of human languages.

Deaf children whose access to usable conventional linguistic input, signed or spoken, is severely limited nevertheless use gesture to communicate. These gestures resemble natural language in that they are structured at the level both of sentence and of word. Although the inclination to use gesture may be traceable to the fact that the deaf children's hearing parents, like all speakers, gesture as they talk, the children themselves are responsible for introducing language-like structure into their gestures. We have explored the robustness of this phenomenon by observing deaf children of hearing parents in two cultures, an American and a Chinese culture, that differ in their child-rearing practices and in the way gesture is used in relation to speech. The spontaneous sign systems developed in these cultures shared a number of structural similarities: patterned production and deletion of semantic elements in the surface structure of a sentence; patterned ordering of those elements within the sentence; and concatenation of propositions within a sentence. These striking similarities offer critical empirical input towards resolving the ongoing debate about the 'innateness' of language in human infants.

The mammalian hypoglossal canal transmits the nerve that supplies the muscles of the tongue. This canal is absolutely and relatively larger in modern humans than it is in the African apes (Pan and Gorilla). We hypothesize that the human tongue is supplied more richly with motor nerves than are those of living apes and propose that canal size in fossil hominids may provide an indication about the motor coordination of the tongue and reflect the evolution of speech and language. Canals of gracile Australopithecus, and possibly Homo habilis, fall within the range of extant Pan and are significantly smaller than those of modern Homo. The canals of Neanderthals and an early ``modern'' Homo sapiens (Skhul 5), as well as of African and European middle Pleistocene Homo (Kabwe and Swanscombe), fall within the range of extant Homo and are significantly larger than those of Pan troglodytes. These anatomical findings suggest that the vocal capabilities of Neanderthals were the same as those of humans today. Furthermore, the vocal abilities of Australopithecus were not advanced significantly over those of chimpanzees whereas those of Homo may have been essentially modern by at least 400,000 years ago. Thus, human vocal abilities may have appeared much earlier in time than the first archaeological evidence for symbolic behavior

Linguistic evidence indicates that the Yeniseian family of languages, spoken in central Siberia, is most closely related to the Na-Dene family of languages spoken, for the most part, in northwestern North America. This hypothesis locates the source of one of the three migrations responsible for the peopling of the Americas.

This article reports on the current state of our efforts to shed light on the origin and evolution of linguistic diversity using synthetic modeling and artificial life techniques. We construct a simple abstract model of a communication system that has been designed with regard to referential signaling in nonhuman animals. We analyze the evolutionary dynamics of vocabulary sharing based on these experiments. The results show that mutation rates, population size, and resource restrictions define the classes of vocabulary sharing. We also see a dynamic equilibrium, where two states, a state with one dominant shared word and a state with several dominant shared words, take turns appearing. We incorporate the idea of the abstract model into a more concrete situation and present an agent-based model to verify the results of the abstract model and to examine the possibility of using linguistic diversity in the field of distributed AI and robotics. It has been shown that the evolution of linguistic diversity in vocabulary sharing will support cooperative behavior in a population of agents.

The evolution of language implies the parallel evolution of an ability to respond appropriately to signals (language understanding) and an ability to produce the appropriate signals in the appropriate circumstances (language production). When linguistic signals are produced to inform other individuals, individuals that respond appropriately to these signals may increase their reproductive chances but it is less clear what the reproductive advantage is for the language producers. We present simulations in which populations of neural networks living in an environment evolve a simple language with an informative function. Signals are produced to help other individuals categorize edible and poisonous mushrooms, in order to decide whether to approach or avoid encountered mushrooms. Language production, while not under direct evolutionary pressure, evolves as a byproduct of the independently evolving perceptual ability to categorize mushrooms.

This article presents a theoretical criticism of current approaches to the study of the evolution of communication. In particular two very common preconceptions about the subject are analysed: the role of natural selection in the definition of the phenomenon and the metaphor of communication as information exchange. An alternative characterization is presented in terms of autopoietic theory which avoids the mentioned preconceptions. In support of this view, the evolution of coordinated activity is studied in a population of artificial agents playing an interactional game. Dynamical modeling of this evolutionary process based on game-theoretic considerations shows the existence of an evolutionarily stable strategy in the total lack of coordinated activity which, however, may be unreachable due to the presence of a periodic attractor. In a computational model of the same game, action coordination evolves, even with individual costs against it, due to the presence of spatial structuring processes. A detailed explanation of this phenomenon, which does not require kin selection, is presented. In an extended game, recursive coordination evolves nontrivially when the participants share all the relevant information, demonstrating that the metaphor of information exchange can be misleading. It is shown that agents engaged in this sort of interaction are able to perform beyond their individual capabilities.

Synergetic models of language structure predict that the length of a word will depend upon various parameters such as its frequency and the number of phonemes in the language. This prediction has been used to explain word length differences within languages, but less often to explain the differences between languages. Here I show that average word length across 12 West African languages is related to the size of the phonological inventory. This is an apparent example of the adaptation of language structure to the efficient communication of information. The hypothesised mechanism by which the relationship evolves are outlined.

The species-specific organizational property of speech is a continual mouth open-close alternation, the two phases of which are subject to continual articulatory modulation. The cycle constitutes the syllable and the open and closed phases are segments - vowels and consonants respectively. The fact that segmental serial ordering errors in normal adults obey syllable structure constraints suggests that syllabic ``Frames'' and segmental ``Content'' elements are separately controlled in the speech production process. The frames may derive from cycles of mandibular oscillation, present in humans from babbling onset, which are responsible for the open-close alternation. These communication-related frames perhaps first evolved when the ingestion-related cyclicities of mandibular oscillation (associated with mastication (chewing) sucking and licking) took on communicative significance as lipsmacks, tonguesmacks and teeth chatters - displays which are prominent in many nonhuman primates. The new role of Broca's area and its surround in human vocal communication may have derived from its evolutionary history as the main cortical center for the control of ingestive processes. The frame and content components of speech may have subsequently evolved separate realizations within two general-purpose primate motor control systems: (1) A motivation-related medial ``intrinsic'' system, including anterior cingulate cortex and the supplementary motor area, for self-generated behavior, formerly responsible for ancestral vocalization control and now also responsible for frames, and (2) a lateral ``extrinsic'' system, including Broca's area and surround, and Wernicke's area, specialized for response to external input (and therefore the emergent vocal learning capacity) and more responsible for Content.

We present a connectionist model that demonstrates how propositional structure can emerge from the interactions among the members of a community of simple cognitive agents. We first describe a process in which agents coordinating their actions and verbal productions with each other in a shared world leads to the development of propositional structures. We then present a simulation model which implements this process for generating propositions from scratch. We report and discuss the behaviour of the model in terms of its ability to produce three properties of propositions: (1) a coherent lexicon characterised by shared form-meaning mappings; (2) conventional structure in the sequences of forms; (3) the prediction of spatial facts. We show that these properties do not emerge when a single individual learns the task alone and conclude that the properties emerge from the demands of the communication task rather than from anything inside the individual agents. We then show that the shared structural principles can be described as a grammar, and discuss the implications of this demonstration for theories concerning the origins of the structure of language.

Recent work in language acquisition has shown how linguistic form emerges from the operation of self-organizing systems. The emergentist framework emphasizes ways in which the formal structures of language emerge from the interaction of social patterns, patterns implicit in the input, and pressures arising from general aspects of the cognitive system. Emergentist models have been developed to study the acquisition of auditory and articulatory patterns during infancy and the ways in which the learning of the first words emerges from the linkage of auditory, articulatory, and conceptual systems. Neural network models have also been used to study the learning of inflectional markings and basic syntactic patterns. Using both neural network modeling and concepts from the study of dynamic systems, it is possible to analyze language learning as the integration of emergent dynamic systems.

The six and a half thousand languages spoken by humankind are very unevenly distributed across the globe. Language diversity generally increases as one moves from the poles toward the equator and is very low in arid environments. Two belts of extremely high language diversity can be identified. One runs through West and Central Africa, while the other covers South and South-East Asia and the Pacific. Most of the world's languages are found in these two areas. This paper attempts to explain aspects of the global distribution of language diversity. It is proposed that a key factor influencing it has been climatic variability. Where the climate allows continuous food production throughout the year, small groups of people can be reliably self-sufficient and so populations fragment into many small languages. Where the variability of the climate is greater, the size of social network necessary for reliable subsistence is larger, and so languages tend to be more widespread. A regression analysis relating the number of languages spoken in the major tropical countries to the variability of their climates is performed and the results support the hypothesis. The geographical patterning of languages has, however, begun to be destroyed by the spread of Eurasian diseases, Eurasian people, and the world economy.

In this article we present new results of a novel computational approach to the interaction of two important cognitive-linguistic phenomena: (1) language learning; and (2) language change over time (diachronic linguistics). We exploit the insight that while language learning takes place at the individual level, language change is more properly regarded as an ensemble property that takes place at the level of populations of language learners. We show by analytical and computer simulation methods that language learning can be regarded as the driving force behind a dynamical systems account of language change. We apply this model to the specific case of historical change from Classical Portuguese to European Portuguese, demonstrating how a particular language learning model coupled with data on the differences between Classical and European Portuguese leads to specific predictions for possible language-change envelopes. The main investigative message of this paper is to show how this methodology can be applied to a specific case, that of Portuguese. The main moral underscores the individual/population difference; we show that simply because an individual will choose a particular grammar does not mean that all other grammars will be eliminated.

In monkeys, the rostral part of ventral premotor cortex (area F5) contains neurons that discharge, both when the monkey grasps or manipulates objects and when it observes the experimenter making similar actions. These neurons (mirror neurons) appear to represent a system that matches observed events to similar, internally generated actions, and in this way forms a link between the observer and the actor. Transcranial magnetic stimulation and positron emission tomography (PET) experiments suggest that a mirror system for gesture recognition also exists in humans and includes Broca's area. We propose here that such an observation/execution matching system provides a necessary bridge from `doing' to `communicating', as the link between actor and observer becomes a link between the sender and the receiver of each message.

The paper proposes a complex adaptive systems approach to the formation of an ontology and a shared lexicon in a group of distributed agents with only local interactions and no central control authority. The underlying mechanisms are explained in some detail and results of some experiments with robotic agents are briefly reported.

The paper proposes a set of principles and a general architecture that may explain how language and meaning may originate and complexify in a group of physically grounded distributed agents. An experimental setup is introduced for concretising and validating specific mechanisms based on these principles. The setup consists of two robotic heads that watch static or dynamic scenes and engage in language games, in which one robot describes to the other what they see. The first results from experiments showing the emergence of distinctions, of a lexicon, and of primitive syntactic structures are reported.

A model of simple agents capable of sending and receiving se- quences of characters and associating them with elements of a set of structured meanings is used to explore the emergence of systematic communication. In computational simulations, each member of a population alternates between learning to interpret the sequences sent by other members, and sending sequences that others learn to interpret. Eventually the agents develop highly coordinated communication systems that incorporate structural regularities reminiscent of those in human languages.

We deal here with the problem of the origin of language from the point of view of pragmatics. Our aim is to show that any scenario of language origin should explain the relevance phenomenon. Why do people feel obliged to be relevant in casual conversation ? Analysing the structure of relevance leads to unexpected conclusions : relevant information is valuable, therefore language seems to be altruistic. As a consequence, from a Darwinian perspective, speakers should be rare and continually prompted for their knowledge. What we observe, however, is the exact opposite : in many situations, speakers repeatedly strive to make their point, while listeners systematically evaluate what they hear. A possible solution to this paradox is that language is not altruistic and that relevant information is traded for status. The observation of spontaneous conversation provides some evidence that supports such a hypothesis.

The paper reports on experiments in which robotic agents and software agents are set up to originate language and meaning. The experiments test the hypothesis that mechanisms for generating complexity commonly found in biosystems, in particular self-organisation, co-evolution, and level formation, also may explain the spontaneous formation, adaptation, and growth in complexity of language.

Simulated evolution is used as a tool for investigating the selective pressures that have influenced the design of animal signalling systems. The biological literature on communication is first reviewed: central concepts such as the handicap principle and the view of signalling as manipulation are discussed. The equation of ``biological function'' with ``adaptive value'' is then defended, along with a workable definition of communication. Evolutionary simulation models are advocated as a way of testing the coherence of a given theory. Contra some ALife enthusiasts, simulations are not alternate worlds worthy of independent study; in fact they fit naturally into a Quinean picture of scientific knowledge as a web of modifiable propositions. Existing simulation work on the evolution of communication is reviewed: much of it consists of simple proofs of concept that fail to make connections with existing theory. A particular model (MacLennan and Burghardt, 1994) of the evolution of referential communication in a co-operative context is replicated and critiqued in detail.

Evolutionary simulations are then presented that cover a range of ecological scenarios; the first is a general model of food- and alarm-calling. In such situations signallers and receivers can have common or conflicting interests; the model allows us to test the idea that a conflict of interests will lead to an arms race of ever more costly signals, whereas common interests will result in signals that are as cheap as possible. The second model is concerned with communication during aggressive interactions. Many animals use signals to settle contests, thus avoiding the costs associated with fighting. Conventional game-theoretic results suggest that the signalling of aggression or of strength will not be evolutionarily stable unless it is physically unfakeable, but some recent models imply that cost-free, arbitrary signals can be reliable indicators of both intent and ability. The simulation, which features continuous-time perception of the opponent's strategy, is an attempt to settle the question. The third model deals with sexual signalling, i.e., elaborate displays that are designed to persuade members of the opposite sex to mate. The results clarify the question of whether such displays are the pointless result of runaway sexual selection, or whether they function as honest and costly indicators of genetic quality.

The models predict the evolution of reliable communication in a surprisingly narrow range of circumstances; a serious gap remains between these predictions and the ethological data. Future directions for simulation work are discussed.