Live Algorithms

A Live Algorithm takes part in improvised, collaborative performance, sharing the same modes of communication and expression as its partners. The device enjoys the same constraints and freedoms as its human associates. A live algorithm would be expected to imitate, develop ideas and, at times, to contribute novelty and surprise, to experiment and take risks, and to assume leadership. Other performers experience the live algorithm as if it were a human, with a sense of validity and belief. Although designing a live algorithm with the ability to imitate and develop shared ideas is already a formidable undertaking, the additional requirement of innovation is an even harder research challenge. We suggest that it is the ability to innovate that distinguishes autonomy from automation and randomness and postulate that novelty and surprise can be explained as an emergent phenomenon. To this end, most current live algorithm research focusses on certain open dynamic systems which model some aspects of a natural system in which emergence is known to occur. Some differences between people and dynamical systems are immediately evident, however. Memory enables performers to revisit past actions and understand relationships; evaluation, followed by learning, leads to improvement; a social context provides encouragement and criticism and a cultural context imparts meaning via a web of shared experience. But dynamical systems can be augmented with memory using a counterpart to the environment-mediated stigmergetic interaction between insects. We speculate if a live algorithm culture could be also created, and if this is the missing ingredient

Collaborative Music Making with Live Algorithms

All Copyright remains with the author © Copyright 2007This paper discusses developments of ENSEMBLE, an interactive improvisation environment based on the Iterated Prisoner’s Dilemma. The main emphasis of this paper is on the interactive version of ENSEMBLE, and its development for the work ‘fr@gm3nT’ [fragment], a collaboration between the author and saxophonist Derek Pascoe. Some of the lessons learned from non real-time, generative versions of ENSEMBLE are also discussed, along with the implications of the approach for algorithmic composition and live interactive computer music performance.Luke Harral

Self-karaoke patterns: an interactive audio-visual system for handsfree live algorithm performance

Self-karaoke Patterns, is an audiovisual study for improvised cello and live algorithms. The work is motivated in part by addressing the practical needs of the performer in ‘handsfree’ live algorithm contexts and in part an aesthetic concern with resolving the tension between conceptual dedication to autonomous algorithms and musical dedication to coherent performance. The elected approach is inspired by recent work investing the role of ‘shape’ in musical performance

Computational Creativity and Live Algorithms

We examine the field of algorithmic composition from the perspective of computational creativity. We begin by introducing the idea of computational creativity as a philosophical perspective. Next, we introduce a method for consideration of the properties of creative systems, the Creative Systems Framework (CSF). We then use the CSF as a starting point for discussion of a system of comparison specific to algorithmic composition as an artistic and technical practice. Finally, we sketch a road map for future developments in algorithmic composition and live coding, in these terms

Creative Computers, Improvisation and Intimacy

Autonomous musical machine partners, live algorithms, are able to collaborate with human improvisers on an equal footing. Adaptability can be a significant factor in human/machine interaction in this context. Intimacy is an additional factor; intimacy might be achieved if human and machine performers can adapt to each other and learn from one another. Previously associated in computer music with ideas of embodiment and HCI, intimacy as more widely understood, refers to the interpersonal process enjoyed between individuals, in which personal self-disclosure finds validation through a partner's response. Real intimacies are learned over time, not designed, and are based upon an evident reciprocity and emergent mutuality. In the context of musical expression, a social rather than a biological/technological discourse can be applied to live algorithms with a capacity for learning. This possibility is explored with reference to the author's various improvisation/composition systems including au(or)a, piano_prosthesis, and oboe_prosthesis

The threnoscope: a musical work for live coding performance

This paper introduces a new direction in the field of artistic live coding where musical works are presented as pieces in the form of a live coding system. The system itself and the code affordances become equivalent to score system in an open musical work for strong improvisation

NN Music: Improvising with a 'Living' Computer

This paper proposes attributes of a living computer music, the product of a live algorithm. It illustrates how these attributes can inform creative design with reference to a real-time system for solo performer-machine collaboration, Neural Network Music, and the PQƒ framework proposed for live algorithms. Improvisation is treated as a classification problem at a high level of musical behaviour which can be measured statistically and train a multilayer perceptron neural network. Network outputs shape a stochastic-based synthesis engine. Mappings are covertly assigned, revisited by both player and machine as a performance develops. As the timing and choice of mapping is unknown, both participants are invited to learn and adapt to a responsive sonic environment which is created afresh on each performance. This offers a novel real-time application of feed-forward neural networks and a challenging, creative technological platform for freely improvised music