Sequence memory constraints give rise to language-like structure through iterated learning

Human language is composed of sequences of reusable elements. The origins of the sequential structure of language is a hotly debated topic in evolutionary linguistics. In this paper, we show that sets of sequences with language-like statistical properties can emerge from a process of cultural evolution under pressure from chunk-based memory constraints. We employ a novel experimental task that is non-linguistic and non-communicative in nature, in which participants are trained on and later asked to recall a set of sequences one-by-one. Recalled sequences from one participant become training data for the next participant. In this way, we simulate cultural evolution in the laboratory. Our results show a cumulative increase in structure, and by comparing this structure to data from existing linguistic corpora, we demonstrate a close parallel between the sets of sequences that emerge in our experiment and those seen in natural language

Layers in the Fabric of Mind: A Critical Review of Cognitive Ontogeny

The essay is critically examines the conceptual problems with the influential modularity model of mind. We shall see that one of the essential characters of modules, namely informational encapsulation, is not only inessential, it ties a knot at a crucial place blocking the solution to the problem of understanding the formation of concepts from percepts (nodes of procedural knowledge). Subsequently I propose that concept formation takes place by modulation of modules leading to cross-representations, which were otherwise prevented by encapsulation. It must be noted that the argument is not against modular architecture, but a variety of an architecture that prevents interaction among modules. This is followed by a brief argument demonstrating that module without modularization, i.e. without developmental history, is impossible. Finally the emerging picture of cognitive development is drawn in the form of the layers in the fabric of mind, with a brief statement of the possible implications

The CHREST architecture of cognition : the role of perception in general intelligence

Original paper can be found at: http://www.atlantis-press.com/publications/aisr/AGI-10/ Copyright Atlantis Press. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.This paper argues that the CHREST architecture of cognition can shed important light on developing artificial general intelligence. The key theme is that "cognition is perception." The description of the main components and mechanisms of the architecture is followed by a discussion of several domains where CHREST has already been successfully applied, such as the psychology of expert behaviour, the acquisition of language by children, and the learning of multiple representations in physics. The characteristics of CHREST that enable it to account for empirical data include: self-organisation, an emphasis on cognitive limitations, the presence of a perception-learning cycle, and the use of naturalistic data as input for learning. We argue that some of these characteristics can help shed light on the hard questions facing theorists developing artificial general intelligence, such as intuition, the acquisition and use of concepts and the role of embodiment

Adults are more efficient in creating and transmitting novel signalling systems than children

Iterated language learning experiments have shown that meaningful and structured signalling systems emerge when there is pressure for signals to be both learnable and expressive. Yet such experiments have mainly been conducted with adults using language-like signals. Here we explore whether structured signalling systems can also emerge when signalling domains are unfamiliar and when the learners are children with their well-attested cognitive and pragmatic limitations. In Experiment 1, we compared iterated learning of binary auditory sequences denoting small sets of meanings in chains of adults and 5-7-year old children. Signalling systems became more learnable even though iconicity and structure did not emerge despite applying a homonymy filter designed to keep the systems expressive. When the same types of signals were used in referential communication by adult and child dyads in Experiment 2, only the adults, but not the children, were able to negotiate shared iconic and structured signals. Referential communication using their native language by 4-5-year old children in Experiment 3 showed that only interaction with adults, but not with peers resulted in informative expressions. These findings suggest that emergence and transmission of communication systems is unlikely to be driven by children, and point to the importance of cognitive maturity and pragmatic expertise of learners as well as feedback-based scaffolding of communicative effectiveness by experts during language evolution

Tracing the Biological Roots of Knowledge

The essay is a critical review of three possible approaches in the theory of knowledge while tracing the biological roots of knowledge: empiricist, rationalist and developmentalist approaches. Piaget's genetic epistemology, a developmentalist approach, is one of the first comprehensive treatments on the question of tracing biological roots of knowledge. This developmental approach is currently opposed, without questioning the biological roots of knowledge, by the more popular rationalist approach, championed by Chomsky. Developmental approaches are generally coherent with cybernetic models, of which the theory of autopoiesis proposed by Maturana and Varela made a significant theoretical move in proposing an intimate connection between metabolism and knowledge. Modular architecture is currently considered more or less an undisputable model for both biology as well as cognitive science. By suggesting that modulation of modules is possible by motor coordination, a proposal is made to account for higher forms of conscious cognition within the four distinguishable layers of the human mind. Towards the end, the problem of life and cognition is discussed in the context of the evolution of complex cognitive systems, suggesting the unique access of phylogeny during the ontogeny of human beings as a very special case, and how the problem cannot be dealt with independent of the evolution of coding systems in nature

Computer Simulation of Musical Evolution: A Lesson from Whales

Simulating musical creativity using computers needs more than the ability to devise elegant computational implementations of sophisticated algorithms. It requires, firstly, an understanding of what phenomena might be regarded as music; and, secondly, an understanding of the nature of such phenomena — including their evolutionary history, their recursive-hierarchic structure, and the mechanisms by which they are transmitted within cultural groups. To understand these issues it is fruitful to compare human music, and indeed human language, with analogous phenomena in other areas of the animal kingdom. Whale song, specifically that of the humpback (Megaptera novaeangeliae), possesses many structural and functional similarities to human music (as do certain types of birdsong). Using a memetic perspective, this paper compares the “musilanguage” of humpbacks with the music of humans, and aims to identify a number of shared characteristics. A consequence of nature and nurture, these commonalities appear to arise partly from certain constraints of perception and cognition (and thus they determine an aspect of the environment within which the “musemes” (musical memes) constituting whale vocalizations and human music is replicated), and partly from the social-emotive-embodied and sexual-selective nature of musemic transmission. The paper argues that Universal-Darwinian forces give rise to uniformities of structure in phenomena we might regard as “music”, irrespective of the animal group — certain primates, cetaceans or birds - within which it occurs. It considers the extent to which whale song might be regarded as creative, by invoking certain criteria used to assess this attribute in human music. On the basis of these various comparisons, the paper concludes by attempting to draw conclusions applicable to those engaged in designing evolutionary music simulation/generation algorithms

Language Evolution, Acquisition, Adaptation and Change

In the twenty‐first century, there are between 6000 and 8000 different languages spoken in the world, all of which are in a continuous state of evolving, by inter‐mixing or stagnating, growing or contracting. This occurs through changes in the population size of the people who use them, the frequency and form of their use in different media, through migration and through inter‐mixing with other languages. As Stadler et al. argue, human languages are a ‘culturally evolving trait’ and when it occurs language change is both sporadic and robust (faithfully replicated) and the main established variants are replaced by new variants. Only about 200 of these disparate languages are in written as well as spoken form, and most, except the popular ones like Mandarin, Spanish, English, Hindi, Arabic, Portuguese, Bengali, and Russian, are in decline of use. But how did language itself evolve and come to be the most important innate tool possessed by people? The complex issue of language evolution continues to perplex because of its associations with culture, social behaviour and the development of the human mind

Editors' Review and Introduction:The Cultural Evolution of Cognition

This topic addresses a question of key interest to cognitive science, namely which factors may have triggered, constrained, or shaped the course of cognitive evolution. It highlights the relevance of culture as a driving force in this process, with a special focus on social learning and language, conceptual tools, and material culture. In so doing, the topic combines two goals: to provide an overview of current empirical and theoretical work leading this field, tailored for a wider cognitive science audience, and to investigate the potential for integrating multiple perspectives across several timescales and levels of analysis, from the microlevel of individual behavior to the macrolevel of cultural change and language diversification. One key purpose is to assess the extent to which the different research approaches can cross‐fertilize each other, thereby also contributing to the advancement of cognitive science more broadly.acceptedVersio

Consciosusness in Cognitive Architectures. A Principled Analysis of RCS, Soar and ACT-R

This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness.\ud To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST).\ud A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems

Neural Dynamics of Learning and Performance of Fixed Sequences: Latency Pattern Reorganizations and the N-STREAMS Model

Fixed sequences performed from memory play a key role in human cultural behavior, especially in music and in rapid communication through speaking, handwriting, and typing. Upon first performance, fixed sequences are often produced slowly, but extensive practice leads to performance that is both fluid and as rapid as allowed by constraints inherent in the task or the performer. The experimental study of fixed sequence learning and production has generated a large database with some challenging findings, including practice-related reorganizations of temporal properties of performance. In this paper, we analyze this literature and identify a coherent set of robust experimental effects. Among these are both the sequence length effect on latency, a dependence of reaction time on sequence length, and practice-dependent lost of the lengths effect on latency. We then introduce a neural network architecture capable of explaining these effects. Called the NSTREAMS model, this multi-module architecture embodies the hypothesis that the brain uses several substrates for serial order representation and learning. The theory describes three such substrates and how learning autonomously modifies their interaction over the course of practice. A key feature of the architecture is the co-operation of a 'competitive queuing' performance mechanism with both fundamentally parallel ('priority-tagged') and fundamentally sequential ('chain-like') representations of serial order. A neurobiological interpretation of the architecture suggests how different parts of the brain divide the labor for serial learning and performance. Rhodes (1999) presents a complete mathematical model as implementation of the architecture, and reports successful simulations of the major experimental effects. It also highlights how the network mechanisms incorporated in the architecture compare and contrast with earlier substrates proposed for competitive queuing, priority tagging and response chaining.Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-92-J-1309, N00014-93-1-1364, N00014-95-1-0409); National Institute of Health (RO1 DC02852