A Subsumption Agent for Collaborative Free Improvisation

This paper discusses the design and evaluation of an artificial agent for collaborative musical free improvisation. The agent provides a means to investigate the underpinnings of improvisational interaction. In connection with this general goal, the system is also used here to explore the implementation of a collaborative musical agent using a specific robotics architecture, Subsumption. The architecture of the system is explained, and its evaluation in an empirical study with expert improvisors is discussed. A follow-up study using a second iteration of the system is also presented. The system design and connected studies bring together Subsumption robotics, ecological psychology, and musical improvisation, and contribute to an empirical grounding of an ecological theory of improvisation

Investigating the cognitive foundations of collaborative musical free improvisation: Experimental case studies using a novel application of the subsumption architecture

This thesis investigates the cognitive foundations of collaborative musical free improvisation. To explore the cognitive underpinnings of the collaborative process, a series of experimental case studies was undertaken in which expert improvisors performed with an artificial agent. The research connects ecological musicology and subsumption robotics, and builds upon insights from empirical psychology pertaining to the attribution of intentionality. A distinguishing characteristic of free improvisation is that no over-arching framework of formal musical conventions defines it, and it cannot be positively identified by sound alone, which poses difficulties for traditional musicology. Current musicological research has begun to focus on the social dimension of music, including improvisation. Ecological psychology, which focuses on the relation of cognition to agent–environment dynamics using the notion of affordances, has been shown to be a promising approach to understanding musical improvisation. This ecological approach to musicology makes it possible to address the subjective and social aspects of improvised music, as opposed to the common treatment of music as objective and neutral. The subjective dimension of musical listening has been highlighted in music cognition studies of cue abstraction, whereby listeners perceive emergent structures while listening to certain forms of music when no structures are identified in advance. These considerations informed the design of the artificial agent, Odessa, used for this study. In contrast to traditional artificial intelligence (AI), which tends to view the world as objective and neutral, behaviour-based robotics historically developed around ideas similar to those of ecological psychology, focused on agent–environment dynamics and the ability to deal with potentially rapidly changing environments. Behaviour-based systems that are designed using the subsumption architecture are robust and flexible in virtue of their modular, decentralised design comprised of simple interactions between simple mechanisms. The competence of such agents is demonstrated on the basis of their interaction with the environment and ability to cope with unknown and dynamic conditions, which suggests the concept of improvisation. This thesis documents a parsimonious subsumption design for an agent that performs musical free improvisation with human co-performers, as well as the experimental studies conducted with this agent. The empirical component examines the human experience of collaborating with the agent and, more generally, the cognitive psychology of collaborative improvisation. The design was ultimately successful, and yielded insights about cognition in collaborative improvisation, in particular, concerning the central relationship between perceived intentionality and affordances. As a novel application of the subsumption architecture, this research contributes to AI/robotics and to research on interactive improvisation systems. It also contributes to music psychology and cognition, as well as improvisation studies, through its empirical grounding of an ecological model of musical interaction

AI Methods in Algorithmic Composition: A Comprehensive Survey

Algorithmic composition is the partial or total automation of the process of music composition by using computers. Since the 1950s, different computational techniques related to Artificial Intelligence have been used for algorithmic composition, including grammatical representations, probabilistic methods, neural networks, symbolic rule-based systems, constraint programming and evolutionary algorithms. This survey aims to be a comprehensive account of research on algorithmic composition, presenting a thorough view of the field for researchers in Artificial Intelligence.This study was partially supported by a grant for the MELOMICS project (IPT-300000-2010-010) from the Spanish Ministerio de Ciencia e Innovación, and a grant for the CAUCE project (TSI-090302-2011-8) from the Spanish Ministerio de Industria, Turismo y Comercio. The first author was supported by a grant for the GENEX project (P09-TIC- 5123) from the Consejería de Innovación y Ciencia de Andalucía

Computational Systems for Music Improvisation

Computational music systems that afford improvised creative interaction in real time are often designed for a specific improviser and performance style. As such the field is diverse, fragmented and lacks a coherent framework. Through analysis of examples in the field we identify key areas of concern in the design of new systems, which we use as categories in the construction of a taxonomy. From our broad overview of the field we select significant examples to analyse in greater depth. This analysis serves to derive principles that may aid designers scaffold their work on existing innovation. We explore successful evaluation techniques from other fields and describe how they may be applied to iterative design processes for improvisational systems. We hope that by developing a more coherent design and evaluation process, we can support the next generation of improvisational music systems

Musical Bodies, Musical Minds

An enactive account of musicality that proposes new ways of thinking about musical experience, musical development in infancy, music and evolution, and more. Musical Bodies, Musical Minds offers an innovative account of human musicality that draws on recent developments in embodied cognitive science. The authors explore musical cognition as a form of sense-making that unfolds across the embodied, environmentally embedded, and sociomaterially extended dimensions that compose the enactment of human worlds of meaning. This perspective enables new ways of understanding musical experience, the development of musicality in infancy and childhood, music's emergence in human evolution, and the nature of musical emotions, empathy, and creativity. Developing their account, the authors link a diverse array of ideas from fields including neuroscience, theoretical biology, psychology, developmental studies, social cognition, and education. Drawing on these insights, they show how dynamic processes of adaptive body-brain-environment interactivity drive musical cognition across a range of contexts, extending it beyond the personal (inner) domain of musical agents and out into the material and social worlds they inhabit and influence. An enactive approach to musicality, they argue, can reveal important aspects of human being and knowing that are often lost or obscured in the modern technologically driven world

Is Knowledge Emerging in the Secrecy of Our Digital Collections?

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Music in Evolution and Evolution in Music

Music in Evolution and Evolution in Music by Steven Jan is a comprehensive account of the relationships between evolutionary theory and music. Examining the ‘evolutionary algorithm’ that drives biological and musical-cultural evolution, the book provides a distinctive commentary on how musicality and music can shed light on our understanding of Darwin’s famous theory, and vice-versa. Comprised of seven chapters, with several musical examples, figures and definitions of terms, this original and accessible book is a valuable resource for anyone interested in the relationships between music and evolutionary thought. Jan guides the reader through key evolutionary ideas and the development of human musicality, before exploring cultural evolution, evolutionary ideas in musical scholarship, animal vocalisations, music generated through technology, and the nature of consciousness as an evolutionary phenomenon. A unique examination of how evolutionary thought intersects with music, Music in Evolution and Evolution in Music is essential to our understanding of how and why music arose in our species and why it is such a significant presence in our lives

Conceptual Representations for Computational Concept Creation

Computational creativity seeks to understand computational mechanisms that can be characterized as creative. The creation of new concepts is a central challenge for any creative system. In this article, we outline different approaches to computational concept creation and then review conceptual representations relevant to concept creation, and therefore to computational creativity. The conceptual representations are organized in accordance with two important perspectives on the distinctions between them. One distinction is between symbolic, spatial and connectionist representations. The other is between descriptive and procedural representations. Additionally, conceptual representations used in particular creative domains, such as language, music, image and emotion, are reviewed separately. For every representation reviewed, we cover the inference it affords, the computational means of building it, and its application in concept creation.Peer reviewe