Constraint-Based Sound-Motion Objects in Music Performance

The aim of this paper is to present principles of constraint-based sound-motion objects in music performance. Sound-motion objects are multimodal fragments of combined sound and sound-producing body motion, usually in the duration range of just a few seconds, and conceived, produced, and perceived as intrinsically coherent units. Sound-motion objects have a privileged role as building blocks in music because of their duration, coherence, and salient features and emerge from combined instrumental, biomechanical, and motor control constraints at work in performance. Exploring these constraints and the crucial role of the sound-motion objects can enhance our understanding of generative processes in music and have practical applications in performance, improvisation, and composition.

Generative Meditations: Exploring Generative Art From the Perspective of Tibetan Buddhist Philosophy

<p>the purpose of this thesis is to document and explore the subjective struggles I have encountered in my own practise as a generative artist rather than to provide an objective overview of computational generative art. Hopefully this process will give some context from the ground up (from an artist’s perspective) to some of the larger questions that I and others in the field are asking about generative art. From the preliminary questions arising from these struggles I begin to explore and develop a generative art practise that primarily focuses on the topics of human experience and ideas directly related to human experience. This is opposed to using generative processes to explore ideas fundamentally based on computation (a-life, emergence, computational creativity, and data etc..). The foundation of, and reasons behind, such a focus are based on the non-realist and non-materialist philosophical tenets of Tibetan Buddhism, in particular the philosophy of the Madhyamika-Prasangika school of thought. The purpose of developing a generative practise based on the philosophy and symbolism of Tibetan Buddhism is to find a method to create personally relevant artwork with a firm foundation in a well established culture of art and philosophy. I might add however, that this isn’t merely a self-reflective exercise but rather it should be of interest to others in the field of (and study of) Generative art to see how this artistic method might be approached from a vastly different philosophical stance to the materialist view that receives the majority of attention in the field.</p>

Generative Meditations: Exploring Generative Art From the Perspective of Tibetan Buddhist Philosophy

<p>the purpose of this thesis is to document and explore the subjective struggles I have encountered in my own practise as a generative artist rather than to provide an objective overview of computational generative art. Hopefully this process will give some context from the ground up (from an artist’s perspective) to some of the larger questions that I and others in the field are asking about generative art. From the preliminary questions arising from these struggles I begin to explore and develop a generative art practise that primarily focuses on the topics of human experience and ideas directly related to human experience. This is opposed to using generative processes to explore ideas fundamentally based on computation (a-life, emergence, computational creativity, and data etc..). The foundation of, and reasons behind, such a focus are based on the non-realist and non-materialist philosophical tenets of Tibetan Buddhism, in particular the philosophy of the Madhyamika-Prasangika school of thought. The purpose of developing a generative practise based on the philosophy and symbolism of Tibetan Buddhism is to find a method to create personally relevant artwork with a firm foundation in a well established culture of art and philosophy. I might add however, that this isn’t merely a self-reflective exercise but rather it should be of interest to others in the field of (and study of) Generative art to see how this artistic method might be approached from a vastly different philosophical stance to the materialist view that receives the majority of attention in the field.</p>

The Challenge of Inferring Unconscious Mental Processes

Studies of unconscious mental processes often compare a performance measure (e.g., some assessment of perception or memory) with a measure of awareness (e.g., a verbal report or forced-choice response) of the critical cue or contingency taken either concurrently or separately. The resulting patterns of bivariate data across participants lend themselves to several analytic approaches for inferring the existence of unconscious mental processes, but it is rare for researchers to consider the underlying generative processes that might cause these patterns. We show that bivariate data are generally insufficient to discriminate single-process models, with a unitary latent process determining both performance and awareness, from dual-process models, comprising distinct latent processes for performance and awareness. Future research attempting to isolate and investigate unconscious processes will need to employ richer types of data and analyses.

Emergence and Algorithmic Information Dynamics of Systems and Observers

Previous work has shown that perturbation analysis in algorithmic information dynamics can uncover generative causal processes of finite objects and quantify each of its element's information contribution to computably constructing the objects. One of the challenges for defining emergence is that the dependency on the observer's previous knowledge may cause a phenomenon to present itself as emergent for one observer at the same time that reducible for another observer. Thus, in order to quantify emergence of algorithmic information in computable generative processes, perturbation analyses may inherit such a problem of the dependency on the observer's previous formal knowledge. In this sense, by formalizing the act of observing as mutual perturbations, the emergence of algorithmic information becomes invariant, minimal, and robust to information costs and distortions, while it indeed depends on the observer. Then, we demonstrate that the unbounded increase of emergent algorithmic information implies asymptotically observer-independent emergence, which eventually overcomes any formal theory that any observer might devise. In addition, we discuss weak and strong emergence and analyze the concepts of observer-dependent emergence and asymptotically observer-independent emergence found in previous definitions and models in the literature of deterministic dynamical and computable systems.

Institutional Change

This chapter reviews the current state of research on change processes from an institutional perspective. It examines the longitudinal progression of research, illustrating the generative processes that drive change, the patterns of change over time, the mechanisms underpinning change, and its key outcomes. It distinguishes variance and process studies and zooms in on process-based research (i.e., temporal progression of event sequences), discussing implications for organizations, and similarities and differences between theoretical models of change. We conclude by noting that our typology of change pathways situates extant research to reveal important blind spots in the literature that require more systematic attention.

Dynamical modules in metabolism, cell and developmental biology

Modularity is an essential feature of any adaptive complex system. Phenotypic traits are modules in the sense that they have a distinguishable structure or function, which can vary (quasi-)independently from its context. Since all phenotypic traits are the product of some underlying regulatory dynamics, the generative processes that constitute the genotype–phenotype map must also be functionally modular. Traditionally, modular processes have been identified as structural modules in regulatory networks. However, structure only constrains, but does not determine, the dynamics of a process. Here, we propose an alternative approach that decomposes the behaviour of a complex regulatory system into elementary activity-functions. Modular activities can occur in networks that show no structural modularity, making dynamical modularity more widely applicable than structural decomposition. Furthermore, the behaviour of a regulatory system closely mirrors its functional contribution to the outcome of a process, which makes dynamical modularity particularly suited for functional decomposition. We illustrate our approach with numerous examples from the study of metabolism, cellular processes, as well as development and pattern formation. We argue that dynamical modules provide a shared conceptual foundation for developmental and evolutionary biology, and serve as the foundation for a new account of process homology, which is presented in a separate contribution by DiFrisco and Jaeger to this focus issue.

Learning by Explaining Orally or In Written Form? Text Difficulty Matters

In this experiment, we examined whether text difficulty moderates the effect of the modality of explaining on students’ learning. Students (N = 115) read a high-difficult and a low-difficult text. Additionally, students generated either a written or an oral explanation. A control group of students retrieved the content. For the low-difficult text, we found no significant differences between conditions. For the high-difficult text, however, oral explaining yielded better comprehension than writing explanations. The retrieval condition showed the lowest performance. Mediation analyses revealed that the effect of explaining modality was mediated by the number of personal references and the comprehensiveness of the generated explanations. Our findings suggest that the effect of explaining modality emerges when students are required to learn from difficult text materials. Furthermore, the findings show that oral explaining is effective, as it triggers distinct generative processes due to increased social presence during explaining.

Dances with Robots

What does it feel like to dance with a robot? How do you choreograph one? Working with robots during three artistic residencies and two research projects has raised questions about agency and generative processes, revealing how dancing with robots may provoke a more interanimate everyday world.