Computational musicology: An Artificial Life approach

Abstract — Artificial Life (A-Life) and Evolutionary Algorithms (EA) provide a variety of new techniques for making and studying music. EA have been used in different musical applications, ranging from new systems for composition and performance, to models for studying musical evolution in artificial societies. This paper starts with a brief introduction to three main fields of application of EA in Music, namely sound design, creativity and computational musicology. Then it presents our work in the field of computational musicology. Computational musicology is broadly defined as the study of Music with computational modelling and simulation. We are interested in developing A-Life-based models to study the evolution of musical cognition in an artificial society of agents. In this paper we present the main components of a model that we are developing to study the evolution of musical ontogenies, focusing on the evolution of rhythms and emotional systems. The paper concludes by suggesting that A-Life and EA provide a powerful paradigm for computational musicology. I

Applying social norms to implicit negotiation among Non-Player Characters in serious games

Abstract-Believable Non Player Characters (NPCs), i.e. artificial characters simulating rational entities, are a great addition to videogames, no matter if used for entertainment or serious reasons. Especially NPCs that represent people in realistic settings need to show plausible behaviors; to this end, one of main issues to be tackled is coordination with other participants, either other NPCs or human players, when performing everyday tasks such as crossing doors, queuing at an office, picking the first free object up from a set, and so on. Much of this coordination happens silently and is driven by social norms that may vary according to culture and context. In this paper, we propose an approach to represent social norms in autonomous agents and enable implicit coordination driven by observations of others' behavior. Our approach does not use central coordinators or a coordination protocol, but rather let each agent take its own decision so to support more realistic interactions with human players. A software architecture and initial experimental results are presented and discussed

Computational and Psycho-Physiological Investigations of Musical Emotions

The ability of music to stir human emotions is a well known fact (Gabrielsson & Lindstrom. 2001). However, the manner in which music contributes to those experiences remains obscured. One of the main reasons is the large number of syndromes that characterise emotional experiences. Another is their subjective nature: musical emotions can be affected by memories, individual preferences and attitudes, among other factors (Scherer & Zentner, 2001). But can the same music induce similar affective experiences in all listeners, somehow independently of acculturation or personal bias? A considerable corpus of literature has consistently reported that listeners agree rather strongly about what type of emotion is expressed in a particular piece or even in particular moments or sections (Juslin & Sloboda, 2001). Those studies suggest that music features encode important characteristics of affective experiences, by suggesting the influence of various structural factors of music on emotional expression. Unfortunately, the nature of these relationships is complex, and it is common to find rather vague and contradictory descriptions. This thesis presents a novel methodology to analyse the dynamics of emotional responses to music. It consists of a computational investigation, based on spatiotemporal neural networks sensitive to structural aspects of music, which "mimic" human affective responses to music and permit to predict new ones. The dynamics of emotional responses to music are investigated as computational representations of perceptual processes (psychoacoustic features) and self-perception of physiological activation (peripheral feedback). Modelling and experimental results provide evidence suggesting that spatiotemporal patterns of sound resonate with affective features underlying judgements of subjective feelings. A significant part of the listener's affective response is predicted from the a set of six psychoacoustic features of sound - tempo, loudness, multiplicity (texture), power spectrum centroid (mean pitch), sharpness (timbre) and mean STFT flux (pitch variation) - and one physiological variable - heart rate. This work contributes to new evidence and insights to the study of musical emotions, with particular relevance to the music perception and emotion research communities

Emergent Rhythmic Structures as Cultural Phenomena Driven by Social Pressure in a Society of Artificial Agents

This thesis studies rhythm from an evolutionary computation perspective. Rhythm is the most fundamental dimension of music and can be used as a ground to describe the evolution of music. More specifically, the main goal of the thesis is to investigate how complex rhythmic structures evolve, subject to the cultural transmission between individuals in a society. The study is developed by means of computer modelling and simulations informed by evolutionary computation and artificial life (A-Life). In this process, self-organisation plays a fundamental role. The evolutionary process is steered by the evaluation of rhythmic complexity and by the exposure to rhythmic material. In this thesis, composers and musicologists will find the description of a system named A-Rhythm, which explores the emerged behaviours in a community of artificial autonomous agents that interact in a virtual environment. The interaction between the agents takes the form of imitation games. A set of necessary criteria was established for the construction of a compositional system in which cultural transmission is observed. These criteria allowed the comparison with related work in the field of evolutionary computation and music. In the development of the system, rhythmic representation is discussed. The proposed representation enabled the development of complexity and similarity based measures, and the recombination of rhythms in a creative manner. A-Rhythm produced results in the form of simulation data which were evaluated in terms of the coherence of repertoires of the agents. The data shows how rhythmic sequences are changed and sustained in the population, displaying synchronic and diachronic diversity. Finally, this tool was used as a generative mechanism for composition and several examples are presented.Leverhulme Trus

Collective Adaptive Systems: Qualitative and Quantitative Modelling and Analysis (Dagstuhl Seminar 14512)

This report documents the program and the outcomes of Dagstuhl Seminar 14512 "Collective Adaptive Systems: Qualitative and Quantitative Modelling and Analysis". Besides presentations on current work in the area, the seminar focused on the following topics: (i) Modelling techniques and languages for collective adaptive systems based on the above formalisms. (ii) Verification of collective adaptive systems. (iii) Humans-in-the-loop in collective adaptive systems

Pervasive Personal Information Spaces

Each user’s electronic information-interaction uniquely matches their information behaviour, activities and work context. In the ubiquitous computing environment, this information-interaction and the underlying personal information is distributed across multiple personal devices. This thesis investigates the idea of Pervasive Personal Information Spaces for improving ubiquitous personal information-interaction. Pervasive Personal Information Spaces integrate information distributed across multiple personal devices to support anytime-anywhere access to an individual’s information. This information is then visualised through context-based, flexible views that are personalised through user activities, diverse annotations and spontaneous information associations. The Spaces model embodies the characteristics of Pervasive Personal Information Spaces, which emphasise integration of the user’s information space, automation and communication, and flexible views. The model forms the basis for InfoMesh, an example implementation developed for desktops, laptops and PDAs. The design of the system was supported by a tool developed during the research called activity snaps that captures realistic user activity information for aiding the design and evaluation of interactive systems. User evaluation of InfoMesh elicited a positive response from participants for the ideas underlying Pervasive Personal Information Spaces, especially for carrying out work naturally and visualising, interpreting and retrieving information according to personalised contexts, associations and annotations. The user studies supported the research hypothesis, revealing that context-based flexible views may indeed provide better contextual, ubiquitous access and visualisation of information than current-day systems