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Computational creativity also known as artificial creativitymechanical creativitycreative computing or creative computation is a multidisciplinary endeavour that is located at the intersection of the fields of artificial intelligencecognitive psychologyphilosophyand the arts.

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The goal of computational creativity is to model, simulate or replicate creativity using a computer, to achieve one of several ends: [1]. The field of computational creativity concerns itself with theoretical and practical issues in the study of creativity.

Art As A Creative Field

Theoretical work on the nature and proper definition of creativity is performed in parallel with practical work on the implementation of systems that exhibit creativity, with one strand of work informing the other. The applied form of computational creativity is known as media synthesis. As measured by the amount of activity in the field e. Creativity is very difficult, perhaps even impossible, to define in objective terms. Is it a state of mind, a talent more info ability, or a Art As A Creative Field Creativity takes many forms in human activity, some eminent sometimes referred to as "Creativity" with a Crdative C and some mundane.

Art As A Creative Field

These are problems that complicate the study of creativity in general, but certain problems attach themselves specifically to computational creativity: [ citation needed ]. Indeed, not all computer theorists would agree with the premise that computers can only do what they are programmed to do [3] —a key point in favor of computational creativity.

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Because no single perspective or definition seems to offer a complete picture of creativity, the AI researchers Newell, Shaw and Simon [4] developed the combination of novelty and usefulness into the cornerstone of a multi-pronged view of creativity, one that uses the following four criteria to categorize a given answer or solution as creative:. Whereas the above reflects a "top-down" approach Ass computational creativity, an alternative thread has developed among "bottom-up" computational psychologists involved in artificial neural network research. During the late s and early s, for example, such generative neural systems were driven by genetic algorithms. Concurrent with such research, Aw number of computational psychologists took the perspective, popularized by Stephen Wolframthat system behaviors perceived as complex, including the mind's creative output, could Art As A Creative Field from what would be considered simple algorithms.

As neuro-philosophical thinking matured, it also became evident that language actually presented an obstacle to producing a scientific model of learn more here, creative or not, since it carried with it so many unscientific aggrandizements that were more uplifting than accurate.

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Thus questions naturally arose as to how "rich," "complex," and "wonderful" creative cognition actually was. Beforeartificial neural networks have been used to model certain aspects of creativity. Peter Todd first trained a neural network to reproduce musical melodies from a training set of musical pieces. Then he used a change algorithm to modify the network's input Creatige.

Art As A Creative Field

The network was able to randomly generate new music in a highly uncontrolled manner. Nguyen and Bernard Widrow[13] Michael I. Jordan and David Rumelhart. In later efforts by Todd, a composer would select a set of melodies that define the melody space, position them on a 2-d plane with a mouse-based graphic interface, and train a connectionist network to produce those melodies, and listen to the new "interpolated" melodies that the network generates corresponding to intermediate points in the 2-d plane.

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More recently a neurodynamical model Art As A Creative Field semantic networks has been developed to study how the connectivity structure of these networks relates to the richness of the semantic constructs, or ideas, they can generate. It was demonstrated that semantic neural networks that have richer semantic dynamics than those with other connectivity structures may provide insight into the important issue of how the physical structure of the brain determines one of the most profound features of the human Creatice — its capacity for creative thought.

Some high-level and philosophical themes recur throughout the field of computational creativity. Margaret Boden [16] [17] refers to creativity that is novel merely to the agent that produces it as "P-creativity" or "psychological creativity"and refers to creativity that Cfeative recognized as novel by society at large as "H-creativity" or "historical creativity".

Stephen Thaler has suggested a new category he calls "V-" or "Visceral creativity" wherein significance is invented to raw sensory inputs to a Creativity Machine architecture, with the "gateway" nets perturbed to produce alternative interpretations, and downstream nets shifting such interpretations to fit the overarching context.]

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