11,995 research outputs found

    Complex Beauty

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    Complex systems and their underlying convoluted networks are ubiquitous, all we need is an eye for them. They pose problems of organized complexity which cannot be approached with a reductionist method. Complexity science and its emergent sister network science both come to grips with the inherent complexity of complex systems with an holistic strategy. The relevance of complexity, however, transcends the sciences. Complex systems and networks are the focal point of a philosophical, cultural and artistic turn of our tightly interrelated and interdependent postmodern society. Here I take a different, aesthetic perspective on complexity. I argue that complex systems can be beautiful and can the object of artification - the neologism refers to processes in which something that is not regarded as art in the traditional sense of the word is changed into art. Complex systems and networks are powerful sources of inspiration for the generative designer, for the artful data visualizer, as well as for the traditional artist. I finally discuss the benefits of a cross-fertilization between science and art

    Searching for surprise

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    Inspired by the notion of surprise for unconventional discovery in computational creativity, we introduce a general search algorithm we name surprise search. Surprise search is grounded in the divergent search paradigm and is fabricated within the principles of metaheuristic (evolutionary) search. The algorithm mimics the self-surprise cognitive process of creativity and equips computational creators with the ability to search for outcomes that deviate from the algorithm’s expected behavior. The predictive model of expected outcomes is based on historical trails of where the search has been and some local information about the search space. We showcase the basic steps of the algorithm via a problem solving (maze navigation) and a generative art task. What distinguishes surprise search from other forms of divergent search, such as the search for novelty, is its ability to diverge not from earlier and seen outcomes but rather from predicted and unseen points in the creative domain considered.This work has been supported in part by the FP7 Marie Curie CIG project AutoGameDesign (project no: 630665).peer-reviewe

    Soft thought (in architecture and choreography)

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    This article is an introduction to and exploration of the concept of ‘soft thought’. What we want to propose through the definition of this concept is an aesthetic of digital code that does not necessarily presuppose a relation with the generative aspects of coding, nor with its sensorial perception and evaluation. Numbers do not have to produce something, and do not need to be transduced into colours and sounds, in order to be considered as aesthetic objects. Starting from this assumption, our main aim will be to reconnect the numerical aesthetic of code with a more ‘abstract’ kind of feeling, the feeling of numbers indirectly felt as conceptual contagions’, that are ‘conceptually felt but not directly sensed. The following pages will be dedicated to the explication and exemplification of this particular mode of feeling, and to its possible definition as ‘soft thought’

    The promises and perils of the neuroscience of creativity.

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    Our ability to think creatively is one of the factors that generates excitement in our lives as it introduces novelty and opens up new possibilities to our awareness which in turn lead to developments in a variety of fields from science and technology to art and culture. While research on the influence of biologically-based variables on creativity has a long history, the advent of modern techniques for investigating brain structure and function in the past two decades have resulted in an exponential increase in the number of neuroscientific studies that have explored creativity. The field of creative neurocognition is a rapidly growing area of research that can appear chaotic and inaccessible because of the heterogeneity associated with the creativity construct and the many approaches through which it can be examined. There are also significant methodological and conceptual problems that are specific to the neuroscientific study of creativity that pose considerable limitations on our capacity to make true advances in understanding the brain basis of creativity. This article explores three key issues that need to be addressed so that barriers in the way of relevant progress being made within the field can be avoided. Are creativity neuroimaging paradigms optimal enough?What makes creative cognition different from normative cognition?Do we need to distinguish between types of creativity
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