Language Evolution and Computation Bibliography

At the onset of vocal development, both songbirds and humans produce variable vocal babbling with broadly distributed acoustic features. Over development, these vocalizations differentiate into the well-defined, categorical signals that characterize adult vocal behaviour. A broadly distributed signal is ideal for vocal exploration, that is, for matching vocal production to the statistics of the sensory input. The developmental transition to categorical signals is a gradual process during which the vocal output becomes differentiated and stable. But does it require categorical input? We trained juvenile zebra finches with playbacks of their own developing song, produced just a few moments earlier, updated continuously over development. Although the vocalizations of these self-tutored (ST) birds were initially broadly distributed, birds quickly developed categorical signals, as fast as birds that were trained with a categorical, adult song template. By contrast, siblings of those birds that received no training (isolates) developed phonological categories much more slowly and never reached the same level of category differentiation as their ST brothers. Therefore, instead of simply mirroring the statistical properties of their sensory input, songbirds actively transform it into distinct categories. We suggest that the early self-generation of phonological categories facilitates the establishment of vocal culture by making the song easier to transmit at the micro level, while promoting stability of shared vocabulary at the group level over generations.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'.

Linguistic universals arise from the interaction between the processes of language learning and language use. A test case for the relationship between these factors is linguistic variation, which tends to be conditioned on linguistic or sociolinguistic criteria. How can we explain the scarcity of unpredictable variation in natural language, and to what extent is this property of language a straightforward reflection of biases in statistical learning? We review three strands of experimental work exploring these questions, and introduce a Bayesian model of the learning and transmission of linguistic variation along with a closely matched artificial language learning experiment with adult participants. Our results show that while the biases of language learners can potentially play a role in shaping linguistic systems, the relationship between biases of learners and the structure of languages is not straightforward. Weak biases can have strong effects on language structure as they accumulate over repeated transmission. But the opposite can also be true: strong biases can have weak or no effects. Furthermore, the use of language during interaction can reshape linguistic systems. Combining data and insights from studies of learning, transmission and use is therefore essential if we are to understand how biases in statistical learning interact with language transmission and language use to shape the structural properties of language.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'.

We offer a new solution to the unsolved problem of how infants break into word learning based on the visual statistics of everyday infant-perspective scenes. Images from head camera video captured by 8 1/2 to 10 1/2 month-old infants at 147 at-home mealtime events were analysed for the objects in view. The images were found to be highly cluttered with many different objects in view. However, the frequency distribution of object categories was extremely right skewed such that a very small set of objects was pervasively present-a fact that may substantially reduce the problem of referential ambiguity. The statistical structure of objects in these infant egocentric scenes differs markedly from that in the training sets used in computational models and in experiments on statistical word-referent learning. Therefore, the results also indicate a need to re-examine current explanations of how infants break into word learning.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'.

In recent years, laboratory studies of cultural evolution have become increasingly prevalent as a means of identifying and understanding the effects of cultural transmission on the form and functionality of transmitted material. The datasets generated by these studies may provide insights into the conditions encouraging, or inhibiting, high rates of innovation, as well as the effect that this has on measures of adaptive cultural change. Here we review recent experimental studies of cultural evolution with a view to elucidating the role of innovation in generating observed trends. We first consider how tasks are presented to participants, and how the corresponding conceptualization of task success is likely to influence the degree of intent underlying any deviations from perfect reproduction. We then consider the measures of interest used by the researchers to track the changes that occur as a result of transmission, and how these are likely to be affected by differing rates of retention. We conclude that considering studies of cultural evolution from the perspective of innovation provides us with valuable insights that help to clarify important differences in research designs, which have implications for the likely effects of variation in retention rates on measures of cultural adaptation.

Evolution is marked by well-defined events involving profound innovations that are known as 'major evolutionary transitions'. They involve the integration of autonomous elements into a new, higher-level organization whereby the former isolated units interact in novel ways, losing their original autonomy. All major transitions, which include the origin of life, cells, multicellular systems, societies or language (among other examples), took place millions of years ago. Are these transitions unique, rare events? Have they instead universal traits that make them almost inevitable when the right pieces are in place? Are there general laws of evolutionary innovation? In order to approach this problem under a novel perspective, we argue that a parallel class of evolutionary transitions can be explored involving the use of artificial evolutionary experiments where alternative paths to innovation can be explored. These 'synthetic' transitions include, for example, the artificial evolution of multicellular systems or the emergence of language in evolved communicating robots. These alternative scenarios could help us to understand the underlying laws that predate the rise of major innovations and the possibility for general laws of evolved complexity. Several key examples and theoretical approaches are summarized and future challenges are outlined.This article is part of the themed issue 'The major synthetic evolutionary transitions'.

Human languages are extraordinarily complex adaptive systems. They feature intricate hierarchical sound structures, are able to express elaborate meanings and use sophisticated syntactic and semantic structures to relate sound to meaning. What are the cognitive mechanisms that speakers and listeners need to create and sustain such a remarkable system? What is the collective evolutionary dynamics that allows a language to self-organize, become more complex and adapt to changing challenges in expressive power? This paper focuses on grammar. It presents a basic cycle observed in the historical language record, whereby meanings move from lexical to syntactic and then to a morphological mode of expression before returning to a lexical mode, and discusses how we can discover and validate mechanisms that can cause these shifts using agent-based models.This article is part of the themed issue 'The major synthetic evolutionary transitions'.

The evolution of life in our biosphere has been marked by several major innovations. Such major complexity shifts include the origin of cells, genetic codes or multicellularity to the emergence of non-genetic information, language or even consciousness. Understanding the nature and conditions for their rise and success is a major challenge for evolutionary biology. Along with data analysis, phylogenetic studies and dedicated experimental work, theoretical and computational studies are an essential part of this exploration. With the rise of synthetic biology, evolutionary robotics, artificial life and advanced simulations, novel perspectives to these problems have led to a rather interesting scenario, where not only the major transitions can be studied or even reproduced, but even new ones might be potentially identified. In both cases, transitions can be understood in terms of phase transitions, as defined in physics. Such mapping (if correct) would help in defining a general framework to establish a theory of major transitions, both natural and artificial. Here, we review some advances made at the crossroads between statistical physics, artificial life, synthetic biology and evolutionary robotics.This article is part of the themed issue 'The major synthetic evolutionary transitions'.

Musicality can be defined as a natural, spontaneously developing trait based on and constrained by biology and cognition. Music, by contrast, can be defined as a social and cultural construct based on that very musicality. One critical challenge is to delineate the constituent elements of musicality. What biological and cognitive mechanisms are essential for perceiving, appreciating and making music? Progress in understanding the evolution of music cognition depends upon adequate characterization of the constituent mechanisms of musicality and the extent to which they are present in non-human species. We argue for the importance of identifying these mechanisms and delineating their functions and developmental course, as well as suggesting effective means of studying them in human and non-human animals. It is virtually impossible to underpin the evolutionary role of musicality as a whole, but a multicomponent perspective on musicality that emphasizes its constituent capacities, development and neural cognitive specificity is an excellent starting point for a research programme aimed at illuminating the origins and evolution of musical behaviour as an autonomous trait.

Iconicity, a resemblance between properties of linguistic form (both in spoken and signed languages) and meaning, has traditionally been considered to be a marginal, irrelevant phenomenon for our understanding of language processing, development and evolution. Rather, the arbitrary and symbolic nature of language has long been taken as a design feature of the human linguistic system. In this paper, we propose an alternative framework in which iconicity in face-to-face communication (spoken and signed) is a powerful vehicle for bridging between language and human sensori-motor experience, and, as such, iconicity provides a key to understanding language evolution, development and processing. In language evolution, iconicity might have played a key role in establishing displacement (the ability of language to refer beyond what is immediately present), which is core to what language does; in ontogenesis, iconicity might play a critical role in supporting referentiality (learning to map linguistic labels to objects, events, etc., in the world), which is core to vocabulary development. Finally, in language processing, iconicity could provide a mechanism to account for how language comes to be embodied (grounded in our sensory and motor systems), which is core to meaningful communication.

The movements we make with our hands both reflect our mental processes and help to shape them. Our actions and gestures can affect our mental representations of actions and objects. In this paper, we explore the relationship between action, gesture and thought in both humans and non-human primates and discuss its role in the evolution of language. Human gesture (specifically representational gesture) may provide a unique link between action and mental representation. It is kinaesthetically close to action and is, at the same time, symbolic. Non-human primates use gesture frequently to communicate, and do so flexibly. However, their gestures mainly resemble incomplete actions and lack the representational elements that characterize much of human gesture. Differences in the mirror neuron system provide a potential explanation for non-human primates' lack of representational gestures; the monkey mirror system does not respond to representational gestures, while the human system does. In humans, gesture grounds mental representation in action, but there is no evidence for this link in other primates. We argue that gesture played an important role in the transition to symbolic thought and language in human evolution, following a cognitive leap that allowed gesture to incorporate representational elements.

Abstract The Paridae family (chickadees, tits and titmice) is an interesting avian group in that species vary in important aspects of their social structure and many species have large and complex vocal repertoires. For this reason, parids represent an important set of species for ...

Artificial grammar learning (AGL) provides a useful tool for exploring rule learning strategies linked to general purpose pattern perception. To be able to directly compare performance of humans with other species with different memory capacities, we developed an AGL task in the visual domain. Presenting entire visual patterns simultaneously instead of sequentially minimizes the amount of required working memory. This approach allowed us to evaluate performance levels of two bird species, kea (Nestor notabilis) and pigeons (Columba livia), in direct comparison to human participants. After being trained to discriminate between two types of visual patterns generated by rules at different levels of computational complexity and presented on a computer screen, birds and humans received further training with a series of novel stimuli that followed the same rules, but differed in various visual features from the training stimuli. Most avian and all human subjects continued to perform well above chance during this initial generalization phase, suggesting that they were able to generalize learned rules to novel stimuli. However, detailed testing with stimuli that violated the intended rules regarding the exact number of stimulus elements indicates that neither bird species was able to successfully acquire the intended pattern rule. Our data suggest that, in contrast to humans, these birds were unable to master a simple rule above the finite-state level, even with simultaneous item presentation and despite intensive training.

Humans are animals that specialize in thinking and knowing, and our extraordinary cognitive abilities have transformed every aspect of our lives. In contrast to our chimpanzee cousins and Stone Age ancestors, we are complex political, economic, scientific and artistic creatures, living in a vast range of habitats, many of which are our own creation. Research on the evolution of human cognition asks what types of thinking make us such peculiar animals, and how they have been generated by evolutionary processes. New research in this field looks deeper into the evolutionary history of human cognition, and adopts a more multi-disciplinary approach than earlier ‘Evolutionary Psychology’. It is informed by comparisons between humans and a range of primate and non-primate species, and integrates findings from anthropology, archaeology, economics, evolutionary biology, neuroscience, philosophy and psychology. Using these methods, recent research reveals profound commonalities, as well striking differences, between human and non-human minds, and suggests that the evolution of human cognition has been much more gradual and incremental than previously assumed. It accords crucial roles to cultural evolution, techno-social co-evolution and gene–culture co-evolution. These have produced domain-general developmental processes with extraordinary power—power that makes human cognition, and human lives, unique.

Abstract Historical inference is at its most powerful when independent lines of evidence can be integrated into a coherent account. Dating linguistic and cultural lineages can potentially play a vital role in the integration of evidence from linguistics, anthropology, archaeology ...

We propose that the cognitive mechanisms that enable the transmission of cultural knowledge by communication between individuals constitute a system of ‘natural pedagogy’ in humans, and represent an evolutionary adaptation along the hominin lineage. We discuss three kinds of arguments that support this hypothesis. First, natural pedagogy is likely to be human-specific: while social learning and communication are both widespread in non-human animals, we know of no example of social learning by communication in any other species apart from humans. Second, natural pedagogy is universal: despite the huge variability in child-rearing practices, all human cultures rely on communication to transmit to novices a variety of different types of cultural knowledge, including information about artefact kinds, conventional behaviours, arbitrary referential symbols, cognitively opaque skills and know-how embedded in means-end actions. Third, the data available on early hominin technological culture are more compatible with the assumption that natural pedagogy was an independently selected adaptive cognitive system than considering it as a by-product of some other human-specific adaptation, such as language. By providing a qualitatively new type of social learning mechanism, natural pedagogy is not only the product but also one of the sources of the rich cultural heritage of our species.

Evolutionary approaches to cultural change are increasingly influential, and many scientists believe that a `grand synthesis' is now in sight. The papers in this Theme Issue, which derives from a symposium held by the AHRC Centre for the Evolution of Cultural Diversity (University College London) in December 2008, focus on how the phylogenetic tree-building and network-based techniques used to estimate descent relationships in biology can be adapted to reconstruct cultural histories, where some degree of inter-societal diffusion will almost inevitably be superimposed on any deeper signal of a historical branching process. The disciplines represented include the three most purely `cultural' fields from the four-fiel' model of anthropology (cultural anthropology, archaeology and linguistic anthropology). In this short introduction, some context is provided from the history of anthropology, and key issues raised by the papers are highlighted.

We examine situations in which linguistic changes have probably been propagated via normal contact as opposed to via conquest, recent settlement and large-scale migration. We proceed then from two simplifying assumptions: first, that all linguistic variation is the result of either diffusion or independent innovation, and, second, that we may operationalize social contact as geographical distance. It is clear that both of these assumptions are imperfect, but they allow us to examine diffusion via the distribution of linguistic variation as a function of geographical distance. Several studies in quantitative linguistics have examined this relation, starting with Seguy (Seguy 1971 Rev. Linguist. Romane 35, 335-357), and virtually all report a sublinear growth in aggregate linguistic variation as a function of geographical distance. The literature from dialectology and historical linguistics has mostly traced the diffusion of individual features, however, so that it is sensible to ask what sort of dynamic in the diffusion of individual features is compatible with Seguy's curve. We examine some simulations of diffusion in an effort to shed light on this question.

Linguists have traditionally represented patterns of divergence within a language family in terms of either a splits model, corresponding to a branching family tree structure, or the wave model, resulting in a (dialect) continuum. Recent phylogenetic analyses, however, have tended to assume the former as a viable idealization also for the latter. But the contrast matters, for it typically reflects different processes in the real world: speaker populations either separated by migrations, or expanding over continuous territory. Since history often leaves a complex of both patterns within the same language family, ideally we need a single model to capture both, and tease apart the respective contributions of each. The network type of phylogenetic method offers this, so we review recent applications to language data. Most have used lexical data, encoded as binary or multi-state characters. We look instead at continuous distance measures of divergence in phonetics. Our output networks combine branch- and continuum-like signals in ways that correspond well to known histories (illustrated for Germanic, and particularly English). We thus challenge the traditional insistence on shared innovations, setting out a new, principled explanation for why complex language histories can emerge correctly from distance measures, despite shared retentions and parallel innovations.

This paper presents an overview of the current state of historical linguistics in Australian languages. Australian languages have been important in theoretical debates about the nature of language change and the possibilities for reconstruction and classification in areas of intensive diffusion. Here are summarized the most important outstanding questions for Australian linguistic prehistory; I also present a case study of the Karnic subgroup of Pama-Nyungan, which illustrates the problems for classification in Australian languages and potential approaches using phylogenetic methods.

'Language shift' is the process whereby members of a community in which more than one language is spoken abandon their original vernacular language in favour of another. The historical shifts to English by Celtic language speakers of Britain and Ireland are particularly well-studied examples for which good census data exist for the most recent 100-120 years in many areas where Celtic languages were once the prevailing vernaculars. We model the dynamics of language shift as a competition process in which the numbers of speakers of each language (both monolingual and bilingual) vary as a function both of internal recruitment (as the net outcome of birth, death, immigration and emigration rates of native speakers), and of gains and losses owing to language shift. We examine two models: a basic model in which bilingualism is simply the transitional state for households moving between alternative monolingual states, and a diglossia model in which there is an additional demand for the endangered language as the preferred medium of communication in some restricted sociolinguistic domain, superimposed on the basic shift dynamics. Fitting our models to census data, we successfully reproduce the demographic trajectories of both languages over the past century. We estimate the rates of recruitment of new Scottish Gaelic speakers that would be required each year (for instance, through school education) to counteract the natural wastage as households with one or more Gaelic speakers fail to transmit the language to the next generation informally, for different rates of loss during informal intergenerational transmission.

In this paper we outline two debates about the nature of human cultural history. The first focuses on the extent to which human history is tree-like (its shape), and the second on the unity of that history (its fabric). Proponents of cultural phylogenetics are often accused of assuming that human history has been both highly tree-like and consisting of tightly linked lineages. Critics have pointed out obvious exceptions to these assumptions. Instead of a priori dichotomous disputes about the validity of cultural phylogenetics, we suggest that the debate is better conceptualized as involving positions along continuous dimensions. The challenge for empirical research is, therefore, to determine where particular aspects of culture lie on these dimensions. We discuss the ability of current computational methods derived from evolutionary biology to address these questions. These methods are then used to compare the extent to which lexical evolution is tree-like in different parts of the world and to evaluate the coherence of cultural and linguistic lineages.

The articles in this theme issue seek to understand the evolutionary bases of social learning and the consequences of cultural transmission for the evolution of human behaviour. In this introductory article, we provide a summary of these articles (seven articles on the experimental exploration of cultural transmission and three articles on the role of gene-culture coevolution in shaping human behaviour) and a personal view of some promising lines of development suggested by the work summarized here.

A growing set of observational studies documenting putative cultural variations in wild animal populations has been complemented by experimental studies that can more rigorously distinguish between social and individual learning. However, these experiments typically examine only what one animal learns from another. Since the spread of culture is inherently a group-level phenomenon, greater validity can be achieved through `diffusion experiments', in which founder behaviours are experimentally manipulated and their spread across multiple individuals tested. Here we review the existing corpus of 33 such studies in fishes, birds, rodents and primates and offer the first systematic analysis of the diversity of experimental designs that have arisen. We distinguish three main transmission designs and seven different experimental/control approaches, generating an array with 21 possible cells, 15 of which are currently represented by published studies. Most but not all of the adequately controlled diffusion experiments have provided robust evidence for cultural transmission in at least some taxa, with transmission spreading across populations of up to 24 individuals and along chains of up to 14 transmission events. We survey the achievements of this work, its prospects for the future and its relationship to diffusion studies with humans discussed in this theme issue and elsewhere.

In this paper, we explore how experimental studies of cultural transmission in adult humans can address general questions regarding the `who, what, when and how' of human cultural transmission, and consequently inform a theory of human cultural evolution. Three methods are discussed. The transmission chain method, in which information is passed along linear chains of participants, has been used to identify content biases in cultural transmission. These concern the kind of information that is transmitted. Several such candidate content biases have now emerged from the experimental literature. The replacement method, in which participants in groups are gradually replaced or moved across groups, has been used to study phenomena such as cumulative cultural evolution, cultural group selection and cultural innovation. The closed-group method, in which participants learn in groups with no replacement, has been used to explore issues such as who people choose to learn from and when they learn culturally as opposed to individually. A number of the studies reviewed here have received relatively little attention within their own disciplines, but we suggest that these, and future experimental studies of cultural transmission that build on them, can play an important role in a broader science of cultural evolution.

The question of how much the outcomes of cultural evolution are shaped by the cognitive capacities of human learners has been explored in several disciplines, including psychology, anthropology and linguistics. We address this question through a detailed investigation of transmission chains, in which each person passes information to another along a chain. We review mathematical and empirical evidence that shows that under general conditions, and across experimental paradigms, the information passed along transmission chains will be affected by the inductive biases of the people involved-the constraints on learning and memory, which influence conclusions from limited data. The mathematical analysis considers the case where each person is a rational Bayesian agent. The empirical work consists of behavioural experiments in which human participants are shown to operate in the manner predicted by the Bayesian framework. Specifically, in situations in which each person's response is used to determine the data seen by the next person, people converge on concepts consistent with their inductive biases irrespective of the information seen by the first member of the chain. We then relate the Bayesian analysis of transmission chains to models of biological evolution, clarifying how chains of individuals correspond to population-level models and how selective forces can be incorporated into our models. Taken together, these results indicate how laboratory studies of transmission chains can provide information about the dynamics of cultural evolution and illustrate that inductive biases can have a significant impact on these dynamics.

The existence of social learning has been confirmed in diverse taxa, from apes to guppies. In order to advance our understanding of the consequences of social transmission and evolution of behaviour, however, we require statistical tools that can distinguish among diverse social learning strategies. In this paper, we advance two main ideas. First, social learning is diverse, in the sense that individuals can take advantage of different kinds of information and combine them in different ways. Examining learning strategies for different information conditions illuminates the more detailed design of social learning. We construct and analyse an evolutionary model of diverse social learning heuristics, in order to generate predictions and illustrate the impact of design differences on an organism's fitness. Second, in order to eventually escape the laboratory and apply social learning models to natural behaviour, we require statistical methods that do not depend upon tight experimental control. Therefore, we examine strategic social learning in an experimental setting in which the social information itself is endogenous to the experimental group, as it is in natural settings. We develop statistical models for distinguishing among different strategic uses of social information. The experimental data strongly suggest that most participants employ a hierarchical strategy that uses both average observed pay-offs of options as well as frequency information, the same model predicted by our evolutionary analysis to dominate a wide range of conditions.

Cumulative cultural evolution is the term given to a particular kind of social learning, which allows for the accumulation of modifications over time, involving a ratchet-like effect where successful modifications are maintained until they can be improved upon. There has been great interest in the topic of cumulative cultural evolution from researchers from a wide variety of disciplines, but until recently there were no experimental studies of this phenomenon. Here, we describe our motivations for developing experimental methods for studying cumulative cultural evolution and review the results we have obtained using these techniques. The results that we describe have provided insights into understanding the outcomes of cultural processes at the population level. Our experiments show that cumulative cultural evolution can result in adaptive complexity in behaviour and can also produce convergence in behaviour. These findings lend support to ideas that some behaviours commonly attributed to natural selection and innate tendencies could in fact be shaped by cultural processes.

The primary goal of this study was to investigate cultural transmission in young children, with specific reference to the phenomenon of overimitation. Diffusion chains were used to compare the imitation of 2- and 3-year-olds on a task in which the initial child in each chain performed a series of relevant and irrelevant actions on a puzzle box in order to retrieve a reward. Children in the chains witnessed the actions performed on one of two boxes, one which was transparent and so the lack of causality of the irrelevant actions was obvious, while the other was opaque and so the lack of causal relevance was not obvious. Unlike previous dyadic research in which children overimitate a model, the irrelevant actions were parsed out early in the diffusion chains. Even though children parsed out irrelevant actions, they showed fidelity to the method used to perform a relevant action both within dyads and across groups. This was true of 3-year-olds, and also 2-year-olds, therefore extending findings from previous research.

This paper assesses whether human communication systems undergo the same progressive adaptation seen in animal communication systems and concrete artefacts. Four experiments compared the fitness of ad hoc sign systems created under different conditions when participants play a graphical communication task. Experiment 1 demonstrated that when participants are organized into interacting communities, a series of signs evolve that enhance individual learning and promote efficient decoding. No such benefits are found for signs that result from the local interactions of isolated pairs of interlocutors. Experiments 2 and 3 showed that the decoding benefits associated with community evolved signs cannot be attributed to superior sign encoding or detection. Experiment 4 revealed that naive overseers were better able to identify the meaning of community evolved signs when compared with isolated pair developed signs. Hence, the decoding benefits for community evolved signs arise from their greater residual iconicity. We argue that community evolved sign systems undergo a process of communicative selection and adaptation that promotes optimized sign systems. This results from the interplay between sign diversity and a global alignment constraint; pairwise interaction introduces a range of competing signs and the need to globally align on a single sign-meaning mapping for each referent applies selection pressure.

Much recent work stresses the role of embodiment and action in thought and reason, and celebrates the power of transmitted cultural and environmental structures to transform the problem-solving activity required of individual brains. By apparent contrast, much work in evolutionary psychology has stressed the selective fit of the biological brain to an ancestral environment of evolutionary adaptedness, with an attendant stress upon the limitations and cognitive biases that result. On the face of it, this suggests either a tension or, at least, a mismatch, with the symbiotic dyad of cultural evolution and embodied cognition. In what follows, we explore this mismatch by focusing on three key ideas: cognitive niche construction; cognitive modularity; and the existence (or otherwise) of an evolved universal human nature. An appreciation of the power and scope of the first, combined with consequently more nuanced visions of the latter two, allow us to begin to glimpse a much richer vision of the combined interactive potency of biological and cultural evolution for active, embodied agents.

Genes and culture represent two streams of inheritance that for millions of years have flowed down the generations and interacted. Genetic propensities, expressed throughout development, influence what cultural organisms learn. Culturally transmitted information, expressed in behaviour and artefacts, spreads through populations, modifying selection acting back on populations. Drawing on three case studies, I will illustrate how this gene-culture coevolution has played a critical role in human evolution. These studies explore (i) the evolution of handedness, (ii) sexual selection with a culturally transmitted mating preference, and (iii) cultural niche construction and human evolution. These analyses shed light on how genes and culture shape each other, and on the significance of feedback mechanisms between biological and cultural processes.

Human language is unique among the communication systems of the natural world: it is socially learned and, as a consequence of its recursively compositional structure, offers open-ended communicative potential. The structure of this communication system can be explained as a consequence of the evolution of the human biological capacity for language or the cultural evolution of language itself. We argue, supported by a formal model, that an explanatory account that involves some role for cultural evolution has profound implications for our understanding of the biological evolution of the language faculty: under a number of reasonable scenarios, cultural evolution can shield the language faculty from selection, such that strongly constraining language-specific learning biases are unlikely to evolve. We therefore argue that language is best seen as a consequence of cultural evolution in populations with a weak and/or domain-general language faculty.

Language is the most important evolutionary invention of the last few million years. It was an adaptation that helped our species to exchange information, make plans, express new ideas and totally change the appearance of the planet. How human language evolved from animal communication is one of the most challenging questions for evolutionary biology. The aim of this paper is to outline the major principles that guided language evolution in terms of mathematical models of evolutionary dynamics and game theory. I will discuss how natural selection can lead to the emergence of arbitrary signs, the formation of words and syntactic communication.

Conflicts of interest arise between signaller and receiver in most kinds of biological communication. Some authors have argued that this conflict is likely to give rise to deceit and exploitation, as receivers lag behind in the coevolutionary 'arms race' with signallers. Others have argued that such manipulation is likely to be short-lived and that receivers can avoid being deceived by paying attention to signals that are costly and hence 'unfakeable.' These two views have been hard to reconcile. Here, we present results from simulations of signal evolution using artificial neural networks, which demonstrate that honesty can coexist with a degree of exploitation. Signal cost ensures that receivers are able to obtain some honest information, but is unable to prevent exploitative signalling strategies from gaining short-term benefits. Although any one receiver bias that is open to exploitation will subsist for only a short period of time once signallers begin to take advantage of it, new preferences of this kind are constantly regenerated through selection and random drift. Hidden preferences and sensory exploitation are thus likely to have an enduring influence on the evolution of honest, costly signals. At the same time, honesty and cost are prerequisites for the evolution of exploitation. When signalling is cost-free, selection cannot act to maintain honesty, and receivers rapidly evolve to ignore signals. This leads to a reduction in the extent of hidden preference, and a consequent loss of potential for exploitation.

Evolutionarily stable strategy (ESS) models of biological signalling are important because the intimate coevolution of signalling and receiving strategies is complicated. Tentative results from a numerical study of error-prone signalling show the value of formal modelling. Error in perception can create discreteness in the distribution of signals produced, and so observed discreteness in nature may call for no more complicated explanation. Further developments in the theory of signalling may include a link with theories of aggression such as the sequential assessment game. The technical device of a 'scratch space' may allow a natural development of 'two-way' information games in which each contestant plays the roles of signaller and receiver simultaneously. This device may also incidentally derive mental states from purely strategic considerations.