The Evolution of Language

Preface

Panel of Reviewers

Contents

Recently in the Vocalize-to-Localize framework (a functional stance just started in the Interaction Studies 2004-2005 issues we edited, Abry et al., 2004), we addressed the unification of two grounding attempts concerning the syllable and the foot in language ontogeny. Can the movement time of the pointing strokes of a child be predicted from her babbling rhythm? The answer for 6 babies (6-18 months) was a 2:1 pointing-to-syllable ratio. Implications for the grounding of the first words within this Pointing Frame will be examined. More tentatively we will suggest that babbling for protophonology together with pointing for protosyntax pave the way to language.

The present paper raises the so far unaddressed question of the neurolinguistic processes underlying grammaticalization operations. Two adaptive mechanisms are presented, based on current research on the subcortical contributions to aspects of higher cognition: The cerebellar-induced Kalman gain reduction in linguistic processing, and the basal ganglionic re-regulation of cortical unification operations.

According to Pragmatics, the speaker's intention in declarative speech is to complete or correct the hearer's belief. But the age at which children begin to produce this type of communication is prior to their success in the ‘false belief’ test. Here, after proposing a solution to the problem's hard version -i.e., to early declarative replies-, I will pose it at the level of language origin. A threat of vicious circle and a basic dilemma will be encountered.

No abstract received.

Although most previous model-based research has not moved beyond first-order semantics, human languages are clearly capable of expressing second-order semantics: the meanings expressed in a sentence do not only consist of conjunctions of first-order predicates but also predicates that take other predicates as an argument. In this paper we report on multi-agent language game experiments in which agents handle second-order semantics. We focus our discussion on how this type of research is able to provide fundamental insights in how properties of human-language-like properties could once have emerged. For recursion, this might have happened as a side-effect of agents trying to reuse previously learned language structure as much as possible.

No abstract received.

We motivate a model of human parsing and ambiguity resolution on the basis of psycholinguistic and typological data. Analysis of spoken and written corpora suggests that ambiguity is a factor in the choice of relativization strategy for English and supports the model's predictions. Within an evolutionary account of language, we predict that languages will adapt over time so that prosodic and syntactic systems are organised to minimize processing cost according to this model.

In the general context of dynamics of social consensus, we study an agent based model for the competition between two socially equivalent languages, addressing the role of bilingualism and social structure. In a regular network, we study the formation of linguistic domains and their interaction across the boundaries. We also analyse the dynamics on a small world network and on a network with community structure. In all cases, a final scenario of dominance of one language and extinction of the other is obtained (dominance-extinction state). In comparison with the regular network, smaller times for extinction are found in the small world network. In the network with communities instead, the average time for extinction does not give a characteristic time for the dynamics, and metastable states are observed at all time scales.

5 to 6 million years ago, 3.5 megabase of DNA duplicated from the long arm of the X to create a hominid-specific stratum on the Y short arm. This “saltation” is a candidate for the speciation event for Australopithecus. Within the transposed block a gene pair -Protocadherin X. and Protocadherin Y - has been subject to accelerated evolution, with 16 amino acid changes in the Y protein and five in the X. The latter include the introduction of two sulphur containing cysteines, that are likely to have changed the function of the molecule. The sequence changes on the X, affecting both males and females, are seen as secondary to chromosomal rearrangements on the Y. (four deletions and a paracentric inversion), the latter representing the initiating events in successive speciations, and the former representing the sexually selected phase of accommodation that establishes a new mate recognition system, with asymmetry (the cerebral torque) the autapomorphy for Homo sapiens.

It is argued that compositionality, hierarchy and recursion, generally acknowledged to be universal features of human languages, can be explained as being emergent properties of the complex dynamics governing the establishment and evolution of a language in a population of language users, mainly on an intra-generational time scale, rather than being the result of a genetic selection process leading to a specialized language faculty that imposes those features upon language or than being mainly a cross-generational cultural phenomenon. This claim is supported with results from a computational language game experiment in which a number of autonomous software agents bootstrap a common compositional and recursive language.

The causal correlations between human genetic variants and linguistic (typological) features could represent the mechanism required for gradual, accretionary models of language evolution. The causal link is mediated by the process of cultural transmission of language across generations in a population of genetically biased individuals. The particular case of Tone, ASPM and Microcephalin is discussed as an illustration. It is proposed that this type of genetically-influenced linguistic bias, coupled with a fundamental role for genetic and linguistic diversities, provides a better explanation for the evolution of language and linguistic universals.

The fact that human beings universally put much energy and conviction in reporting events in daily conversations demands an explanation. After having observed that the selection of reportable events is based on unexpectedness and emotion, we make a few suggestions to show how the existence of narrative behaviour can be consistent with the socio-political theory of the origin of language.

The emergence of modern cultural behaviors in Homo sapiens 150,000-50,000 years ago is often explained by a change in the faculty of language, such as the development of recursive syntax or autonomous speech. In this paper, I argue that the link between modern sapiens behaviors and language evolution has never been made convincingly and that a change in the faculty of language can hardly account for the whole range of new behaviors that appear with Homo sapiens. I propose that the domain-general cognitive ability that psychologists call level-2 perspective-taking — an ability closely related to higher theory of mind and metalinguistic awareness — is more parsimonious in explaining modern sapiens behaviors.

The author presents a reexamination of the origins of Preferred Argument Structure (Du Bois 1987, 2002). Conversation data from English are provided, which contradict the putative cognitive motivations of PAS suggested in the literature. The distributional tendencies in the data examined suggest that PAS is epiphenomal and due to extralinguistic factors that could be construed to predate language. Since ligatures between PAS and the evolution of case have been noted in the literature (e.g. Jäger 2007), it is suggested that the motivations for PAS merit further investigation. Finally, it is noted that the data presented reflect another plausible motivation, along with those already found in the literature, for the typological dominance of nominative-accusative patterns, vis-à-vis absolutive-ergative ones.

It is widely assumed that long-distance dependencies between elements are a unique feature of human language. Here we review recent evidence of long-distance correlations in sequences produced by non-human species and discuss two evolutionary scenarios for the evolution of human language in the light of these findings. Though applying their methodological framework, we conclude that some of Hauser, Chomsky and Fitch's central claims on language evolution are put into question to a different degree within each of those scenarios.

This paper examines the relationship between grammatical complexity and complexity in culture, technology and civilization. Colloquial Malay/Indonesian, with its simple nearly Isolating-Monocategorial-Associational grammar, fulfils most functions of a complex society, thereby demonstrating that IMA grammar suffices to support most aspects of modern life. Thus, most of the additional complexity of grammar is not necessary for the maintenance of contemporary civilization, and archeological evidence will never be able to prove the existence of language beyond IMA complexity.

This paper presents a simulation study exploring the role of cultural transmission in intention sharing (the ability to establish shared intentions in communications). This ability has been argued to be human-unique, and the lack of it has deprived animals of the possibility of developing human language. Our simulation results show that the adequate level of this ability to trigger a communal language is not very high, and that cultural transmission can indirectly optimize the average level of this ability in the population. This work extends the current discussion on the human-uniqueness of some language-related abilities, and provides better understanding on the role of cultural transmission in language evolution.

This paper presents a simulation study to explore the role of the naming game in social structure, which is nearly neglected by contemporary studies from statistical physics that mainly discuss the dynamics of language games in predefined mean-field or complex networks. Our foci include the dynamics of the naming game under a simple distance restriction, and the origin and evolution of primitive social clusters as well as their languages under this restriction. This study extends the current work on the role of social structure in language games, and provides better understanding on the self-organizing process of lexical conventionalization during cultural transmission.

The typological distribution of case marking systems presents a puzzle which some linguists have tried to solve in terms of the preferences of individuals. In this paper I highlight some flaws in these approaches, and argue that the typological facts are best dealt with from a diachronic perspective. Processes which could plausibly have given rise to case systems need not have any relation to hypothesised individual preferences concerning case marking. This divergence between putative individual preferences and reasons for the development of linguistic structures undermines the notion that generally typological facts can be informatively illuminated as optimal solutions to aggregated individual preferences.

Recent work modelling the development of communication systems has suggested that linguistic structure may reflect cognitive structures through the repeated effect of biased learning, the language adapting to conform to the learning preferences of its users. However, the notion that an individual's learning is biased can be cashed out in numerous ways. This paper argues that different ideas of what a “learning bias” is produce different population level effects. Biased learning may result in the population's maintenance of structures disfavoured by the bias (cultural inertia) which we can think of as arising through a variety of diachronic processes. Without clear articulations of the relevant diachronic processes and an empirically sound notion of biased learning, the assumption that linguistic structure reflects individuals' language learning psychology is premature.

We argue that studying grammaticalisation is useful to evolutionary linguists, if we abstract away from linguistic description to the underlying cognitive mechanisms. We set out a unified approach to grammaticalisation that allows us to identify these mechanisms, and argue that they could indeed be sufficient for the initial emergence of linguistic signal-meaning associations.

In holistic theories of protolanguage, a vital step is the fractionation process where holistic utterances are broken down into segments, and segments associated with semantic components. One problem for this process may be the occurrence of counterexamples to any segment-meaning connection. The actual abundance of such counterexamples is a contentious issue (Smith, 2006; Tallerman, 2007). Here I present calculations of the prevalence of counterexamples in model languages. It is found that counterexamples are indeed abundant, much more numerous than positive examples for any plausible holistic language.

‘The passage from the state of nature to the civil state produces a very remarkable change in man, by substituting justice for instinct in his conduct, and giving his actions the morality they had formerly lacked. Then only, when the voice of duty takes the place of physical impulses and right of appetite, does man, who so far had considered only himself, find that he is forced to act on different principles, and to consult his reason before listening to his inclinations’.

Over their evolutionary history, languages most likely increased in complexity from simple signals to protolanguages to complex syntactic structures. This paper investigates processes for increasing linguistic complexity while maintaining communicability across a population. We assume that higher linguistic communicability (more accurate information exchange) increases participants' effectiveness in coordination-based tasks. Interaction, needed for learning others' languages and for converging to communicability, bears a cost. There is a threshold of interaction (learning) effort beyond which (the coordination payoff of) linguistic convergence either doesn't pay or is pragmatically impossible. Our central findings, established mainly through simulation, are: 1) There is an effort-dependent “frontier of tractability” for agreement on a language that balances linguistic complexity against linguistic diversity in a population. To remain below some specific bound on collective convergence effort, either a) languages must be simpler, or b) their initial average communicability must be higher. To stay below such a pragmatic effort limit, even agents who have the ultimate capability for complex languages must not invent them from the start or they won't be able to communicate; they must start simple and grow complexity in a staged process. 2) Such a staged approach to increasing complexity, in which agents initially converge on simple languages and then use these to “scaffold” greater complexity, can outperform initially-complex languages in terms of overall effort to convergence. This performance gain improves with more complex final languages.

Over the last decade, computational models and simulations have been used to explore whether words could have emerged in the earliest stages of language evolution through a process of self-organisation in a population. In this paper, a new model of this family is presented, with two major differences from previous models. First, the world consists of an infinite number of objects, while remaining easily manipulable. Second, the agents' categories are based on prototypes, and their structure reflects the environments in which they are acquired and used. Simulation results reveal that, as in previous models, coherent lexicons still generally emerge, but they are sensitive to certain model conditions, including the world structure.

Due to the nature of the subject, the field of language evolution has to rely largely on theoretical considerations. A coherent fundamental framework for approaching language evolution has to relate principles of evolution of complex traits with those governing the organization of cognitive processes, communication and natural language architecture. We suggest that by treating the language faculty as a complex trait with predefined functional interfaces, it is possible to delineate the evolutionary forces that have led to the emergence of natural language. We analyze embedding and recursion in communication, and propose a conceptual prerequisite for natural language and fully symbolic reference: a hierarchical way of conceptualization termed ‘conceptual embedding’ (the ability to nest concepts within concepts). We go on to hypothesize that, initially, the selective force driving the development of the language faculty was towards enhanced conceptualization of reality. According to this scenario, the invention of linguistic communication was a secondary event, dependent on conceptual embedding which supports the sophisticated conceptual underpinnings of linguistic meaning.

No abstract received.

In this paper we will describe an artificial life model that is used to provide an evolutionary grounding for metacommunicative interaction (MCI)—utterance acts in which conversationalists acknowledge understanding or request clarification. Specifically, we ran artificial life experiments on populations of foraging agents who are able to communicate about entities in a simulated environment, where the main difference between the populations is in their MCI capability. Populations which possess MCI capabilities were quantitatively compared with those that lack them with respect to their adaptability in diverse environments. These experiments reveal some clear differences between MCI-realised populations—that learn words using MCI—and MCI-non-realised population—that learn words solely by introspection, where the main finding using this model is that in an increasingly complex language, MCI has overwhelming adaptive power and importance. These results demonstrate in a very clear way how adaptive MCI can be in primordial settings of language use.

This paper presents a simulation model of self-organizing lexical networks. Its starting point is the notion of an association game in which the impact of varying community models is studied on the emergence of lexical networks. The paper reports on experiments whose results are in accordance with findings in the framework of the naming game. This is done by means of a multilevel network model in which the correlation of social and of linguistic networks is studied.

In this paper I propose that the crucial step in the evolution of complex subordinate syntax out of simple paratactic expressions consists in the use of certain grammatical elements (notably, deictic pronouns) for referring to events and other abstract entities. I argue that the development of complex sentences is made possible by event reference together with the predicate argument structure of simple sentences. As a consequence, the evolution towards syntactic complexity can be explained without assuming an alleged syntactic transformation of adjoined sentences into complex subordinate sentential structures.

We demonstrate that polysemous links have a profound impact on the organization of the semantic graph, conforming it as a small-world network, based on the data from WordNet and A Thesaurus of Old English. We show that the words with higher frequency and therefore with higher number of meanings construct the higher level of the hypernymy tree and this architecture is robust through the times. We then set our argumentation in an evolutionary perspective. We also suggest that the small-world topology of the brain has enhanced the small-world semantic configuration.

Within a semiogenetic theory of the language sign (SGT), I claim that human speech emerged and evolved as a consequence of the implementation of an unconscious, somatotopically mapped, self-referential body-naming strategy. This strategy would notably have involved recruiting the cyclical, open-close mandibular movements of non-linguistic, goal-orientated oral activities such as biting and chewing, and of pre-linguistic oral activities such as primitive calling and shouting, for purposes of articulated communication. Specifically, the occlusive sounds produced by these open-close movements may have come to function metonymically (the sound for the movement) as initial ‘building blocks’ on which to construct, by syllabification and consonant accretion, fully linguistic signs ‘naming’ the speech organs concerned, their movements and positions relative to one another, and their immediate physiological environment. The resulting signs, vectoring submorphemic iconicity, may then have been extended by conceptual transfer to denote other parts of the body exhibiting cyclical, goal-orientated, open-close movements, including the hands, characterized by their prehensile function, and the eyes, characterized by the opening and closing of their lids.

The erroneous notion … has been that the intermediate stages in the evolution of structures must be useless – the old saw of ‘What use is half a leg or half an eye?’ (Carroll, 2005, 170-171).

We present a series of studies investigating the formation, generative power, and evolution of toponyms (i.e. topographic names). The domain chosen for this project is the spatial concepts related to places in an environment, one of the key sets of concepts to be grounded in autonomous agents. Concepts for places cannot be directly perceived as they require knowledge of relationships between locations in space, with representations inferred from ambiguous sensory data acquired through exploration. A generative toponymic language game has been developed to allow the agents to interact, forming concepts for locations and spatial relations. The studies demonstrate how a grounded generative toponymic language can form and evolve in a population of agents interacting through language games. Initially, terms are grounded in simple spatial concepts directly experienced by the agents. A generative process then enables the agents to learn about and refer to locations beyond their direct experience, enabling concepts and toponyms to co-evolve. The significance of this research is the demonstration of grounding for both experienced and novel concepts, using a generative process, applied to spatial locations.

The defining problem of animal signalling theory is how reliable communication systems remain stable. The problem comes into sharp focus when signals take an arbitrary form, as human words do. Many researchers, including many in evolutionary linguistics, assume that the Handicap Principle is the only recognised solution to this paradox, and hence conclude that the process that underpins reliability in humans must be exceptional. However, this assumption is false: there are many examples of cheap yet reliable signals in nature, and corresponding evolutionary processes that might explain such examples have been identified. This paper briefly reviews the various processes that ay stabilise communication and hence suggests a three-way classification: signals may be kept honest either by (i) being an index, where meaning is tied to form; (ii) handicaps, in which costs are paid by the honest; or (iii) deterrents, in which costs are paid by the dishonest. Of these, the latter seems by far the most likely: humans are able to assess individual reputation, and hence hold the threat of social exclusion against those who signal unreliably.

There are two possible sources of structure in language: biological evolution of the language faculty, or cultural evolution of language itself. Two recent models (Griffiths & Kalish, 2005; Kirby, Dowman, & Griffiths, 2007) make alternative claims about the relationship between innate bias and linguistic structure: either linguistic structure is largely determined by cultural factors (Kirby et al., 2007), with strength of innate bias being relatively unimportant, or the nature and strength of innate machinery is key (Griffiths & Kalish, 2005). These two competing possibilities rest on different assumptions about the learning process. We extend these models here to include a treatment of biological evolution, and show that natural selection for communication favours those conditions where the structure of language is primarily determined by cultural transmission.

General physical laws are evident as universal syntactic principles governing a computational system of the human language. The optimal space filling condition has to be satisfied in every system of efficient growth. This principle can be attested in syntax, exemplified as the Fibonacci (Fib)-patterns where each new term is the sum of the two that precede it. This rule accounts for the essential features of syntactic trees: limitations imposed on the number of arguments, and phase formation in derivations. The article provides a functional explanation of binary branching, labeling, and two types of Merge. It is shown that in contrast with other Fib-based systems of natural growth syntactic constituents are the instances of both discreteness and continuity.

We show that artificial language evolution involves the interplay of two opposing forces: pressure toward simple representations imposed by the dynamics of collective learning, and pressure towards complex representations imposed by requirements of agents' tasks. The push-pull of these two forces results in the emergence of a language that is balanced: “simple but not too simple.” We introduce the classification game to study the emergence of these balanced languages and their properties. Our agents use artificial neural networks to learn how to solve tasks, and a simple counting algorithm to simultaneously learn a language as a form-meaning mapping. We show that task-language coupling drives the simplicity-complexity balance, and that both compositional and holistic languages can emerge.

Language is typically argued (or assumed) to be an adaptive trait in the Homo lineage, and various specific selection pressures are offered to explain why language would have increased fitness in a population. However, it is incoherent to discuss ‘language’ as a monolithic entity: the set of properties that comprise the full, complex language faculty almost certainly evolved independently, and any pressure that ‘buys’ one of these properties does not necessarily entail the others. Some recent work on kin selection starts by discussing the evolution of speech, but then moves on to the selective value of the exchange of information without indicating how our ancestors got from vocalization to propositions. This is too large a leap, and more specific mechanisms must be proposed if the hypotheses are to be seriously considered.

We combine information theory and cross-situational learning to develop a novel metric for quantifying the degree of regularity in the mappings between signals and meanings that can be inferred from exposure to language in context. We illustrate this metric using the results of two artificial language learning experiments, which show that learners are sensitive, with a high level of individual variation, to systematic regularities in the input. Analysing language using this measure of regularity allows us to explore in detail how language learning and language use can both generate linguistic variation, leading to language change, and potentially complexify language structure, leading to qualitative language evolution.

This paper investigates the relationship between embodied interaction and symbolic communication. We refer to works by Iizuka & Ikegami and Marroco & Nolfi as the examples of simulating EC (embodied communicating) agents, and argue their differences in terms of joint attention, a class of communication between cognitive agents. Then we introduce a new simulation to bridge the gap between the two models; with the new model we demonstrate the two pathways to establishing agents' coordinating behaviors. Based on the simulation results, we explain the typology of sentences (such as ‘declarative’, ‘imperative’ and ‘exclamative’ sentences) from a communicative point of view, which challenges the traditional views of formalizing grammar.

The Chomsky Hierarchy (CH) gives a first approximation as to where human syntax lies in an abstract logical space: the generating device accepting appropriate languages should be slightly more powerful than a standard Push-Down Automaton (a PDA+), although for familiar reasons not much more so. An evolutionary study of syntax ought to give us some clues as to how a PDA+ could have emerged in brains. The goal of my talk is to provide an approach to this question that is informed about contemporary considerations in the Evo-Devo paradigm and, especially, standard results in the study of syntax.

This paper presents a computational system that handles the grounding, the formation, the interpretation and the conceptualisation of rich, compositional meaning for use in grounded, multi-agent simulations of the emergence and evolution of artificial languages. Compositional meaning is deconstructed in terms of semantic building blocks which bundle a semantic function together with the relevant grounding and learning methods. These blocks are computationally modelled as procedural constraints, while the compositional meaning is declaratively represented as constraint programs. The flexibility of the data flow in such programs is utilized to adaptively deal with interpretation and learning. The conceptualisation is performed by a sub-system that composes suitable constraint programs. The various methods used for managing the combinatorial explosion are discussed.

This paper shows how experiments on artificial language evolution can provide highly relevant results for important debates in linguistic theories. It reports on a series of experiments that investigate how semantic roles can emerge in a population of artificial embodied agents and how these agents can build a network of constructions. The experiment also includes a fully operational implementation of how event-specific participant-roles can be fused with the semantic roles of argument-structure constructions and thus contributes to the linguistic debate on how the syntax-semantics interface is organized.

In current literature, a number of standard lines of evidence reemerge in support of the hypothesis that the initial, “bootstrapping” stage of the evolution of language was gestural. However, one specific feature of gestural communication consistent with this hypothesis has been given surprisingly little attention. The visual modality makes gestural signals more secret than vocal signals (lack of broadcast transmission). The high relevance of secrecy is derived from the fundamental constraint on language evolution: the transfer of honest messages itself is a form of cooperation, and therefore not a naturally evolutionarily stable strategy. Consequently, greater secrecy of gestural communication constitutes a potentially important factor that should not fail to be represented in more comprehensive models of the emergence of protolanguage.

We examine the social prerequisites for symbolic communication by studying a language game embedded within a signaling game, in which cooperation is possible but unenforced, and agents have incentive to deceive. Despite this incentive, and even with persistent cheating, naming conventions can still arise from strictly local interactions, as long as agents employ sufficient mechanisms to detect deceit. However, unfairly antagonistic strategies can undermine lexical convergence. Simulated agents are shown to evolve trust relations simultaneously with symbolic communication, suggesting that human language need not be predicated upon existing social relationships, although the cognitive capacity for social interaction seems essential. Thus, language can develop given a balance between restrained deception and revocable trust. Unconditional cooperation and outright altruism are not necessary.

Agents in the process of bootstrapping a shared lexicon face immense uncertainty. The problem that an agent cannot point to meaning but only to objects, represents one of the core aspects of the problem. Even with a straightforward representation of meaning, such as a set of boolean features, the hypothesis space scales exponential in the number of primitive features. Furthermore, data suggests that human learners grasp aspects of many novel words after only a few exposures. We propose a model that can handle the exponential increase in uncertainty and allows scaling towards very large meaning spaces. The key novelty is that word learning or bootstrapping should not be viewed as a mapping task, in which a set of forms is to be mapped onto a set of (predefined) concepts. Instead we view word learning as a process in which the representation of meaning gradually shapes itself, while being usable in interpretation and production almost instantly.

The iterated learning model (ILM), in which a language comes about via communication pressures exerted over successive generations of agents, has attracted much attention in recent years. Its importance lies in the focus on cultural emergence as opposed to biological evolution. The ILM simplifies a compositional language as the compression of an object space, motivated by a poverty of stimulus—as not all objects in the space will be encountered by an individual in its lifetime. However, in the original ILM, every agent ‘magically’ has a complete understanding of the surrounding object space, which weakens the relevance to natural language evolution. In this paper, we define each agent's meaning space as an internal self-organising map, allowing it to remain personal and potentially unique. This strengthens the parallels to real language as the agent's omniscience and ‘mind-reading’ abilities that feature in the original ILM are removed. Additionally, this improvement motivates the compression of the language through a poverty of memory as well as a poverty of stimulus. Analysis of our new implementation shows maintenance of a compositional (structured) language. The effect of a (previously-implicit) generalisation parameter is also analysed; when each agent is able to generalise over a larger number of objects, a more stable compositional language emerges.

Deacon (2003) has suggested that one of the key factors of language evolution is not characterized by increase of genetic contribution, often known as the Baldwin effect, but rather the opposite: decrease of the contribution. This process is named the reverse Baldwin effect. In this paper, we will examine how through a subprocess of the reverse Baldwin effect can be triggered by the niche-constructing aspect of language.

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Author Index