299:, seeing the latter as a form of creativity far more radical, challenging, and rarer than the former. Following the criteria from Newell and Simon elaborated above, we can see that both forms of creativity should produce results that are appreciably novel and useful (criterion 1), but exploratory creativity is more likely to arise from a thorough and persistent search of a well-understood space (criterion 3) -- while transformational creativity should involve the rejection of some of the constraints that define this space (criterion 2) or some of the assumptions that define the problem itself (criterion 4). Boden's insights have guided work in computational creativity at a very general level, providing more an inspirational touchstone for development work than a technical framework of algorithmic substance. However, Boden's insights are also the subject of formalization, most notably in the work by Geraint Wiggins.
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characters so that their search for a solution could be tracked and recorded. The MINSTREL system represents a complex elaboration of this basic approach, distinguishing a range of character-level goals in the story from a range of author-level goals for the story. Systems like
Bringsjord's BRUTUS elaborate these ideas further to create stories with complex interpersonal themes like betrayal. Nonetheless, MINSTREL explicitly models the creative process with a set of Transform Recall Adapt Methods (TRAMs) to create novel scenes from old. The MEXICA model of Rafael PĂ©rez y PĂ©rez and Mike Sharples is more explicitly interested in the creative process of storytelling, and implements a version of the engagement-reflection cognitive model of creative writing.
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963:. ANGELINA is a system for creatively developing video games in Java by Michael Cook. One important aspect is Mechanic Miner, a system that can generate short segments of code that act as simple game mechanics. ANGELINA can evaluate these mechanics for usefulness by playing simple unsolvable game levels and testing to see if the new mechanic makes the level solvable. Sometimes Mechanic Miner discovers bugs in the code and exploits these to make new mechanics for the player to solve problems with.
258:. In the new approach, there are two neural networks, one of which is supplying training patterns to another. 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.
613:, James Martin, Dan Fass, John Barnden, and Mark Lee have developed knowledge-based approaches to the processing of metaphors, either at a linguistic level or a logical level. Tony Veale and Yanfen Hao have developed a system, called Sardonicus, that acquires a comprehensive database of explicit similes from the web; these similes are then tagged as bona-fide (e.g., "as hard as steel") or ironic (e.g., "as hairy as a
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children with communication disabilities. Some limited progress has been made in generating humour that involves other aspects of natural language, such as the deliberate misunderstanding of pronominal reference (in the work of Hans Wim
Tinholt and Anton Nijholt), as well as in the generation of humorous acronyms in the HAHAcronym system of Oliviero Stock and Carlo Strapparava.
914:, which has been continuously developed and augmented since 1973. Though formulaic, Aaron exhibits a range of outputs, generating black-and-white drawings or colour paintings that incorporate human figures (such as dancers), potted plants, rocks, and other elements of background imagery. These images are of a sufficiently high quality to be displayed in reputable galleries.
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already known to the system are filtered at this stage. This body of potentially creative constructs is then evaluated, to determine which are meaningful and useful and which are not. This two-phase structure conforms to the
Geneplore model of Finke, Ward and Smith, which is a psychological model of creative generation based on empirical observation of human creativity.
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Gil
Weinberg of Georgia Tech, has demonstrated jazz improvisation. Virtual improvisation software based on researches on stylistic modeling carried out by Gerard Assayag and Shlomo Dubnov include OMax, SoMax and PyOracle, are used to create improvisations in real-time by re-injecting variable length sequences learned on the fly from the live performer.
803:(CBR) approach to generating poetic formulations of a given input text via a composition of poetic fragments that are retrieved from a case-base of existing poems. Each poem fragment in the ASPERA case-base is annotated with a prose string that expresses the meaning of the fragment, and this prose string is used as the retrieval key for each fragment.
1067:. Nonetheless, some generative principles are more general than others, leading some advocates to claim that certain computational approaches are "general theories". Stephen Thaler, for instance, proposes that certain modalities of neural networks are generative enough, and general enough, to manifest a high degree of creative capabilities.
621:"); similes of either type can be retrieved on demand for any given adjective. They use these similes as the basis of an on-line metaphor generation system called Aristotle that can suggest lexical metaphors for a given descriptive goal (e.g., to describe a supermodel as skinny, the source terms "pencil", "whip", "
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The artist Krasi Dimtch (Krasimira
Dimtchevska) and the software developer Svillen Ranev have created a computational system combining a rule-based generator of English sentences and a visual composition builder that converts sentences generated by the system into abstract art. The software generates
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originated as a system for overpainting digital images of a given scene in a choice of different painting styles, colour palettes and brush types. Given its dependence on an input source image to work with, the earliest iterations of the
Painting Fool raised questions about the extent of, or lack of,
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patterns of language often through individual innovation, while pattern-forming creativity refers to creativity via conformity to language rules rather than breaking them, creating convergence, symmetry and greater mutuality between interlocutors through their interactions in the form of repetitions.
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Computational creativity is increasingly being discussed in the innovation and management literature as the recent development in AI may disrupt entire innovation processes and fundamentally change how innovations will be created. Philip
Hutchinson highlights the relevance of computational creativity
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have been used to model certain aspects of creativity. Peter Todd (1989) 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 parameters. The network was able to randomly generate new music in
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While traditional computational approaches to creativity rely on the explicit formulation of prescriptions by developers and a certain degree of randomness in computer programs, machine learning methods allow computer programs to learn on heuristics from input data enabling creative capacities within
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Whereas the above reflects a top-down approach to computational creativity, an alternative thread has developed among bottom-up computational psychologists involved in artificial neural network research. During the late 1980s and early 1990s, for example, such generative neural systems were driven by
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allowed to make a robot that can create and play a multitude of orchestrated melodies, so-called "coherent" in any musical style. All outdoor physical parameter associated with one or more specific musical parameters, can influence and develop each of these songs (in real-time while listening to the
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has written a software system called "Experiments in
Musical Intelligence" (or "EMI") that is capable of analyzing and generalizing from existing music by a human composer to generate novel musical compositions in the same style. EMI's output is convincing enough to persuade human listeners that its
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Some computational success has been achieved with the blending model by extending pre-existing computational models of analogical mapping that are compatible by virtue of their emphasis on connected semantic structures. In 2006, Francisco Câmara
Pereira presented an implementation of blending theory
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Creativity research in jazz has focused on the process of improvisation and the cognitive demands that this places on a musical agent: reasoning about time, remembering and conceptualizing what has already been played, and planning ahead for what might be played next. The robot Shimon, developed by
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has performed a quantitative analysis of blend structure in
English and found that "the degree of recognizability of the source words and that the similarity of source words to the blend plays a vital role in blend formation." The results were validated through a comparison of intentional blends to
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and introduced the concept of “self-innovating artificial intelligence” (SAI) to describe how companies make use of AI in innovation processes to enhance their innovative offerings. SAI is defined as the organizational utilization of AI with the aim of incrementally advancing existing or developing
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Some researchers feel that creativity is a complex phenomenon whose study is further complicated by the plasticity of the language we use to describe it. We can describe not just the agent of creativity as "creative" but also the product and the method. Consequently, it could be claimed that it is
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The field of computational creativity concerns itself with theoretical and practical issues in the study of creativity. 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
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projects) but rather on the explanation of the psychological processes leading to human creativity and the reproduction of data collected in psychology experiments. So far, this project has been successful in providing an explanation for incubation effects in simple memory experiments, insight in
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The criterion that creative products should be novel and useful means that creative computational systems are typically structured into two phases, generation and evaluation. In the first phase, novel (to the system itself, thus P-Creative) constructs are generated; unoriginal constructs that are
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In early 2016, a global team of researchers explained how a new computational creativity approach known as the Digital Synaptic Neural Substrate (DSNS) could be used to generate original chess puzzles that were not derived from endgame databases. The DSNS is able to combine features of different
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While much of computational creativity research focuses on independent and automatic machine-based creativity generation, many researchers are inclined towards a collaboration approach. This human-computer interaction is sometimes categorized under the creativity support tools development. These
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Fauconnier and Turner describe a collection of optimality principles that are claimed to guide the construction of a well-formed integration network. In essence, they see blending as a compression mechanism in which two or more input structures are compressed into a single blend structure. This
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The combinatorial perspective allows us to model creativity as a search process through the space of possible combinations. The combinations can arise from composition or concatenation of different representations, or through a rule-based or stochastic transformation of initial and intermediate
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Mathematically, the same set of arguments against creativity has been made by Chaitin. Similar observations come from a Model Theory perspective. All this criticism emphasizes that computational creativity is useful and may look like creativity, but it is not real creativity, as nothing new is
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from some basic scenarios provided by the user (e.g., these scenarios allow the system to infer that objects closer to the viewing plane should be larger and more color-saturated, while those further away should be less saturated and appear smaller). Artistically, the images now created by the
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Art") of Penousal Machado. NEvAr uses a genetic algorithm to derive a mathematical function that is then used to generate a coloured three-dimensional surface. A human user is allowed to select the best pictures after each phase of the genetic algorithm, and these preferences are used to guide
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system, which can generate a wide range of puns that are consistently evaluated as novel and humorous by young children. An improved version of JAPE has been developed in the guise of the STANDUP system, which has been experimentally deployed as a means of enhancing linguistic interaction with
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In the seminal work of applied linguist Ronald Carter, he hypothesized two main creativity types involving words and word patterns: pattern-reforming creativity, and pattern-forming creativity. Pattern-reforming creativity refers to creativity by the breaking of rules, reforming and reshaping
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Traditional computers, as mainly used in the computational creativity application, do not support creativity, as they fundamentally transform a set of discrete, limited domain of input parameters into a set of discrete, limited domain of output parameters using a limited set of computational
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Computational creativity in the music domain has focused both on the generation of musical scores for use by human musicians, and on the generation of music for performance by computers. The domain of generation has included classical music (with software that generates music in the style of
722:. ZeitGeist has been extended to generate neologisms of its own; the approach combines elements from an inventory of word parts that are harvested from WordNet, and simultaneously determines likely glosses for these new words (e.g., "food traveller" for "gastronaut" and "time traveller" for "
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Substantial work has been conducted in this area of linguistic creation since the 1970s, with the development of James Meehan's TALE-SPIN system. TALE-SPIN viewed stories as narrative descriptions of a problem-solving effort, and created stories by first establishing a goal for the story's
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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 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
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Like jokes, poems involve a complex interaction of different constraints, and no general-purpose poem generator adequately combines the meaning, phrasing, structure and rhyme aspects of poetry. Nonetheless, Pablo Gervás has developed a noteworthy system called ASPERA that employs a
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systems aim to provide an ideal framework for research, integration, decision-making, and idea generation. Recently, deep learning approaches to imaging, sound and natural language processing, resulted in the modeling of productive creativity development frameworks.
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functions. As such, a computer cannot be creative, as everything in the output must have been already present in the input data or the algorithms. Related discussions and references to related work are captured in work on philosophical foundations of simulation.
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automatically indefinite number of different images using different color, shape and size palettes. The software also allows the user to select the subject of the generated sentences or/and the one or more of the palettes used by the visual composition builder.
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objects (e.g. chess problems, paintings, music) using stochastic methods in order to derive new feature specifications which can be used to generate objects in any of the original domains. The generated chess puzzles have also been featured on YouTube.
654:). Other mapping-based approaches include Sapper, which situates the mapping process in a semantic-network model of memory. Analogy is a very active sub-area of creative computation and creative cognition; active figures in this sub-area include
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Boden also distinguishes between the creativity that arises from an exploration within an established conceptual space, and the creativity that arises from a deliberate transformation or transcendence of this space. She labels the former as
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Theoretical approaches concern the essence of creativity. Especially, under what circumstances it is possible to call the model a "creative" if eminent creativity is about rule-breaking or the disavowal of convention. This is a variant of
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to realize some aspects of blending theory in a practical form; his example domains range from the linguistic to the visual, and the latter most notably includes the creation of mythical monsters by combining 3-D graphical models.
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created a convolutional neural network that uses neural representations to separate and recombine content and style of arbitrary images which is able to turn images into stylistic imitations of works of art by artists such as a
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Margaret Boden focused on the first two of these criteria, arguing instead that creativity (at least when asking whether computers could be creative) should be defined as "the ability to come up with ideas or artifacts that are
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computer vision program, created to detect faces and other patterns in images with the aim of automatically classifying images, which uses a convolutional neural network to find and enhance patterns in images via algorithmic
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Painting Fool appear on a par with those created by Aaron, though the extensible mechanisms employed by the former (constraint satisfaction, etc.) may well allow it to develop into a more elaborate and sophisticated painter.
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Humour is an especially knowledge-hungry process, and the most successful joke-generation systems to date have focussed on pun-generation, as exemplified by the work of Kim Binsted and Graeme Ritchie. This work includes the
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Mihali Csikszentmihalyi argued that creativity had to be considered instead in a social context, and his DIFI (Domain-Individual-Field Interaction) framework has since strongly influenced the field. In DIFI, an
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Previously, the community of computational creativity has held a dedicated workshop, the International Joint Workshop on Computational Creativity, every year since 1999. Previous events in this series include:
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The process of analogical reasoning has been studied from both a mapping and a retrieval perspective, the latter being key to the generation of novel analogies. The dominant school of research, as advanced by
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Todd, P.M. (1992). A connectionist system for exploring melody space. In Proceedings of the 1992 International Computer Music Conference (pp. 65–68). San Francisco: International Computer Music Association.
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in which a selected projection of elements from both input spaces are combined; inferences arising from this combination also reside here, sometimes leading to emergent structures that conflict with the
335:, the spectrum of products to be developed with SAI will broaden from simple to increasingly complex. This implies that computational creativity leads to a shift of creativity-related skills for humans.
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compression operates on the level of conceptual relations. For example, a series of similarity relations between the input spaces can be compressed into a single identity relationship in the blend.
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Szegedy, Christian; Liu, Wei; Jia, Yangqing; Sermanet, Pierre; Reed, Scott E.; Anguelov, Dragomir; Erhan, Dumitru; Vanhoucke, Vincent; Rabinovich, Andrew (2015). "Going deeper with convolutions".
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to determine which glosses are meaningful and which neologisms have not been used before; this search identifies the subset of generated words that are both novel ("H-creative") and useful.
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the computer programs. Especially, deep artificial neural networks allow to learn patterns from input data that allow for the non-linear generation of creative artefacts. Before 1989,
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A great deal, perhaps all, of human creativity can be understood as a novel combination of pre-existing ideas or objects. Common strategies for combinatorial creativity include:
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Karimi, Pegah; Maher, Mary Lou; Davis, Nicholas; Grace, Kazjon (2019-06-24). "Deep Learning in a Computational Model for Conceptual Shifts in a Co-Creative Design System".
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Indeed, not all computer theorists would agree with the premise that computers can only do what they are programmed to do—a key point in favor of computational creativity.
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The International Conference on Computational Creativity (ICCC) occurs annually, organized by The Association for Computational Creativity. Events in the series include:
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a highly uncontrolled manner. In 1992, Todd extended this work, using the so-called distal teacher approach that had been developed by Paul Munro,
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2886:"Methods, systems and software for generating sentences, and visual and audio compositions representing said sentences" Canadian Patent 2704163
2704:(1987), "Experiments in Music Intelligence." In Proceedings of the International Computer Music Conference, San Francisco: Computer Music Assn.
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The blending of multiple word forms is a dominant force for new word creation in language; these new words are commonly called "blends" or "
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609:" The computational study of these phenomena has mainly focused on interpretation as a knowledge-based process. Computationalists such as
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Cockburn, I. M., Henderson, R., & Stern, S. (2018). The impact of artificial intelligence on innovation: An exploratory analysis. In
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Law, Locky (2019). "Creativity and television drama: a corpus-based multimodal analysis of pattern-reforming creativity in House M.D.".
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has had some notable successes in the creation of both abstract art and representational art. A well-known program in this domain is
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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:
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successive phases, thereby pushing NEvAr's search into pockets of the search space that are considered most appealing to the user.
674:-style analogy problems; their approach achieves a score that compares well with average scores achieved by humans on these tests.
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has been well studied, but these creative aspects of everyday language have yet to be incorporated with any robustness or scale.
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does, from its own limited imagination. Images in this vein include cityscapes and forests, which are generated by a process of
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Helie, S.; Sun, R. (2010). "Incubation, insight, and creative problem solving: A unified theory and a connectionist model".
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is the first computer that composes from scratch, and produces final scores that professional interpreters can play. The
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Some high-level and philosophical themes recur throughout the field of computational creativity, for example as follows.
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876:, the technology behind Iamus, is able to generate pieces in different styles of music with a similar level of quality.
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Comparing a familiar object to a superficially unrelated and semantically distant concept (e.g., "Makeup is the Western
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Gries, Stefan T. (2004-01-21). "Shouldn't it be breakfunch? A quantitative analysis of blend structure in English".
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Hutchinson, P. (2020). "Reinventing innovation management: the impact of self-innovating artificial intelligence".
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Using an iconic image from one domain in a domain for an unrelated or incongruous idea or product (e.g., using the
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Language provides continuous opportunity for creativity, evident in the generation of novel sentences, phrasings,
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of stock conventions and image-schemas that allow the input spaces to be understood from an integrated perspective
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Wiggins, Geraint (2006). "A Preliminary Framework for Description, Analysis and Comparison of Creative Systems".
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new products, based on insights from continuously combining and analyzing multiple data sources. As AI becomes a
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To better understand human creativity and to formulate an algorithmic perspective on creative behavior in humans.
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Herremans, Dorien; Chuan, Ching-Hua; Chew, Elaine (2017). "A Functional Taxonomy of Music Generation Systems".
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and interprets them relative to their local context in Knowledge (XXG) and relative to specific word senses in
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in problem-solving. The emphasis of this computational creativity project is not on performance per se (as in
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Mark Turner and Gilles Fauconnier propose a model called Conceptual Integration Networks that elaborates upon
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can be used to generate blended or crossover representations that capture a combination of different inputs.
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as "P-creativity" (or "psychological creativity"), and refers to creativity that is recognized as novel
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IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, June 7–12, 2015
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Gatys, Leon A.; Ecker, Alexander S.; Bethge, Matthias (2015). "A Neural Algorithm of Artistic Style".
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as well as work by Lakoff and Johnson, by synthesizing ideas from Cognitive Linguistic research into
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Comprehending and Generating Apt Metaphors: A Web-driven, Case-based Approach to Figurative Language
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CCSMC 2016, 17–19 June, University of Huddersfield, UK. Keynotes: Geraint Wiggins and Graeme Bailey.
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Artificial Intelligence and Literary Creativity. Inside the Mind of BRUTUS, a Storytelling Machine.
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Jordan, M.I.; Rumelhart, D.E. (1992), "Forward models: Supervised learning with a distal teacher",
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To design programs that can enhance human creativity without necessarily being creative themselves.
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Bharucha, J.J.; Todd, P.M. (1989). "Modeling the perception of tonal structure with neural nets".
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Iqbal, Azlan; Guid, Matej; Colton, Simon; Krivec, Jana; Azman, Shazril; Haghighi, Boshra (2016).
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described as "The first major work composed by a computer and performed by a full orchestra".
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Tolk, Andreas (2013). "Truth, Trust, and Turing – Implications for Modeling and Simulation".
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150:. If a machine can do only what it was programmed to do, how can its behavior ever be called
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Todd, P.M., and Loy, D.G. (Eds.) (1991). Music and connectionism. Cambridge, MA: MIT Press.
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ICCC 2010, Lisbon, Portugal. Keynote/Invited Talks: Nancy J Nersessian and Mary Lou Maher
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that are easily understood, and some have found their way to the dictionary. The area of
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Blending two superficially different objects or genres (e.g., a sci-fi story set in the
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Veale, Tony (2006), "Tracking the Lexical Zeitgeist with Knowledge (XXG) and WordNet",
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Compressing two incongruous scenarios into the same narrative to get a joke (e.g., the
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NEUROGEN, musical composition using genetic algorithms and cooperating neural networks
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Delegating Creativity: Use of Musical Algorithms in Machine Listening and Composition
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Barnden, John (1992). "Belief in Metaphor: Taking Commonsense Psychology Seriously".
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Anh Vo, Thuc; Carter, Ronald (2010), "What can a corpus tell us about creativity?",
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rules are then used to combine these fragments into a well-formed poetic structure.
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joke "Women are always using men to advance their careers. Damned anthropologists!")
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The Digital Synaptic Neural Substrate: A New Approach to Computational Creativity
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Proceedings of ECAI'2006, the 17th European Conference on Artificial Intelligence
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2181:"From hangry to mansplain: spend a little 'me time' with the latest OED update"
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Werbos, P.J. (1989), "Neural networks for control and system identification",
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Munro, P. (1987), "A dual backpropagation scheme for scalar-reward learning",
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problem solving, and reproducing the overshadowing effect in problem solving.
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or SME, the MAC/FAC retrieval engine (Many Are Called, Few Are Chosen), ACME (
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image to sell cars, or to advertise the dangers of smoking-related impotence).
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The 1st Conference on Computer Simulation of Musical Creativity will be held
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Fauconnier, Gilles, Turner, Mark (2007). "Conceptual Integration Networks".
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Adding a new and unexpected feature to an existing concept (e.g., adding a
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2557:
1514:
Todd, P.M. (1989). "A connectionist approach to algorithmic composition".
565:. Native speakers of morphologically rich languages frequently create new
2864:
The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music
2469:
1883:
Gabriel, A.; Monticolo, D.; Camargo, M.; Bourgault, M. (September 2016).
1501:, Second International Conference on Artificial Neural Networks: 309-313.
1002:
873:
711:
550:
534:
170:
The answer is novel and useful (either for the individual or for society)
108:
85:
2144:"Creativity and Artificial Intelligence: A Conceptual Blending Approach"
1697:"The truck backer-upper: An example of self-learning in neural networks"
3264:
3153:
1627:
1535:
1046:
1009:
that allows users to create unique artistic images by their algorithm.
1006:
998:
719:
622:
554:
538:
477:
A first input space (contains one conceptual structure or mental space)
401:
3216:. Intelligent Systems Reference Library. Vol. 44. pp. 1–26.
2931:
2108:
Veale, Tony, O'Donoghue, Diarmuid (2007). "Computation and Blending".
208:
of societal works from which an individual might be later influenced.
3372:
Noorderlicht: Margaret Boden and Stephen Thaler on Creative Computers
3190:
3020:"This algorithm can create a new Van Gogh or Picasso in just an hour"
2935:
2768:
Assayag, GĂ©rard; Bloch, George; Cont, Arshia; Dubnov, Shlomo (2010),
2303:"MEXICA: A computer model of a cognitive account of creative writing"
967:
835:
808:
546:
2665:
2631:, vol. 14, Journal of Knowledge-Based Systems, pp. 181–188
1619:
1559:"Towards Machine Learning as an Enabler of Computational Creativity"
1527:
179:
The answer comes from clarifying a problem that was originally vague
3101:
2656:
1944:
3313:
2957:
2505:, Humor: International Journal of Humor Research, 16(3) pp 297–314
944:
911:
781:
More than iron, more than lead, more than gold I need electricity.
542:
530:
390:
383:
223:
173:
The answer demands that we reject ideas we had previously accepted
36:
3214:
Ontology, Epistemology, and Teleology for Modeling and Simulation
1005:
in about an hour. Their algorithm is put into use in the website
666:. Also worthy of note here is Peter Turney and Michael Littman's
843:
839:
745:
as a reference corpus, Locky Law has performed an extraction of
562:
3046:"This algorithm can create an imitation Van Gogh in 60 minutes"
2310:
Journal of Experimental and Theoretical Artificial Intelligence
1021:
Creativity is also useful in allowing for unusual solutions in
783:
I need it more than I need lamb or pork or lettuce or cucumber.
2999:
Mordvintsev, Alexander; Olah, Christopher; Tyka, Mike (2015).
2980:
Mordvintsev, Alexander; Olah, Christopher; Tyka, Mike (2015).
1836:"A literature review on individual creativity support systems"
1074:
917:
Other software artists of note include the NEvAr system (for "
671:
522:
394:
2829:, article sur l'invention Medal de BĂ©atrice Perret du Cray],
2625:
An expert system for the composition of formal Spanish poetry
2454:"Children's evaluation of computer-generated punning riddles"
1993:"Can computer models help us to understand human creativity?"
1483:
Feldman, D.H.; Csikszentmihalyi, Mihali; Gardner, H. (1994),
1041:-based computational model that allows for the simulation of
2982:"DeepDream – a code example for visualizing Neural Networks"
2412:
Falkenhainer, Brian, Forbus, Ken and Gentner, Dedre (1989).
1423:
Design and Planning II-Computers in Design and Communication
1485:
Changing the World: A Framework for the Study of Creativity
1342:
The Arts and Computational Culture: Real and Virtual Worlds
1147:
ICCC 2022: Free University of Bozen-Bolzano, Bolzano, Italy
883:
In the field of musical composition, the patented works by
200:
produces works whose novelty and value are assessed by the
3356:, SEHR, volume 4, issue 2: Constructions of the Mind, 1995
1436:
Newell, Allen, Shaw, J. G., and Simon, Herbert A. (1963),
347:
Placing a familiar object in an unfamiliar setting (e.g.,
232:
with the prompt "an astronaut riding a horse, by da Vinci"
176:
The answer results from intense motivation and persistence
480:
A second input space (to be blended with the first input)
129:
The applied form of computational creativity is known as
3120:. SpringerBriefs in Cognitive Computation. Switzerland:
1885:"Creativity support systems: A systematic mapping study"
959:
An emerging area of computational creativity is that of
851:
music is human-generated to a high level of competence.
1209:
IJWCC 2006, Riva del Garda, Italy, as part of ECAI'2006
1188:
ICCC 2011, Mexico City, Mexico. Keynote: George E Lewis
1179:
ICCC 2014, Ljubljana, Slovenia. Keynote: Oliver Deussen
2414:"The structure-mapping engine: Algorithm and examples"
2259:
The Creative Process: A Computer Model of Storytelling
1132:
created, just transformed in well-defined algorithms.
989:
appearance in the deliberately over-processed images.
2867:, Natural Computing Series, Berlin: Springer Verlag,
1778:
Creative cognition: Theory, research and applications
3249:. Cambridge Tracts in Theoretical Computer Science.
1182:
ICCC 2013, Sydney, Australia. Keynote: Arne Dietrich
1176:
ICCC 2015, Park City, Utah, US. Keynote: Emily Short
1144:
ICCC 2023: University of Waterloo in Ontario, Canada
1926:
The economics of artificial intelligence: An agenda
1834:Wang, Kai; Nickerson, Jeffrey V. (September 2017).
1200:
IJWCC 2003, Acapulco, Mexico, as part of IJCAI'2003
166:categorize a given answer or solution as creative:
943:has been extended to create novel images, much as
274:Margaret Boden refers to creativity that is novel
3001:"Inceptionism: Going Deeper into Neural Networks"
2499:HAHAcronym: Humorous agents for humorous acronyms
1185:ICCC 2012, Dublin, Ireland. Keynote: Steven Smith
2343:A Computational Model of Metaphor Interpretation
1960:"How Generative AI Can Augment Human Creativity"
1669:Ninth Annual Conference of the Cognitive Science
1557:Mateja, Deborah; Heinzl, Armin (December 2021).
1206:IJWCC 2005, Edinburgh, UK, as part of IJCAI'2005
1203:IJWCC 2004, Madrid, Spain, as part of ECCBR'2004
282:as "H-creativity" (or "historical creativity").
3071:"GitXiv – A Neural Algorithm of Artistic Style"
2452:Binsted, K., Pain, H., and Ritchie, G. (1997),
2166:Language and Creativity: The Art of Common Talk
1150:ICCC 2021: Mexico City, Mexico (Virtual due to
862:played a piece for full orchestra, included in
779:
2861:Machado, Penousal; Romero, Juan, eds. (2008),
2812:, Newton Lee (Ed.), Digital Da Vinci, Springer
2751:"Computer composer honours Turing's centenary"
2301:PĂ©rez y PĂ©rez, Rafael, Sharples, Mike (2001).
1287:Intrinsic motivation (artificial intelligence)
1215:IJWCC 2008, Madrid, Spain, a stand-alone event
902:Computational creativity in the generation of
854:In the field of contemporary classical music,
766:In terms of linguistic research in neologism,
2179:Martin, Katherine Connor (January 30, 2018).
2079:, London: Hutchinson, and New York: Macmillan
1157:ICCC 2020, Coimbra, Portugal (Virtual due to
1058:Debate about "general" theories of creativity
220:Machine learning for computational creativity
8:
2827:«Génération automatique d'œuvres numériques»
2791:"A Robot Named Shimon Wants To Jam With You"
2515:: CS1 maint: multiple names: authors list (
2496:Stock, Oliviero, Strapparava, Carlo (2003),
2481:: CS1 maint: multiple names: authors list (
2437:: CS1 maint: multiple names: authors list (
2397:: CS1 maint: multiple names: authors list (
2326:: CS1 maint: multiple names: authors list (
2286:: CS1 maint: multiple names: authors list (
2261:, Hillsdale, NJ: Lawrence Erlbaum Associates
2212:The Routledge Handbook of Corpus Linguistics
2126:: CS1 maint: multiple names: authors list (
2103:
2101:
2060:: CS1 maint: multiple names: authors list (
2027:: CS1 maint: multiple names: authors list (
1797:: CS1 maint: multiple names: authors list (
1563:IEEE Transactions on Artificial Intelligence
1509:
1507:
1463:
1461:
1450:: CS1 maint: multiple names: authors list (
2276:, Hillsdale NJ: Lawrence Erlbaum Associates
1928:(pp. 115-146). University of Chicago Press.
1817:IEEE Transactions on Engineering Management
1775:Finke, R., Ward, T., and Smith, S. (1992),
1212:IJWCC 2007, London, UK, a stand-alone event
286:Exploratory and transformational creativity
3265:"Association for Computational Creativity"
1735:, Handbook of Creativity, pp 351–373
811:is an example of such a software project.
757:which appeared in the scripts of American
161:Defining creativity in computational terms
3180:
3100:
2956:
2655:
2013:Fauconnier, Gilles, Turner, Mark (2007),
1943:
1851:
1759:
1574:
792:The Policeman's Beard Is Half Constructed
737:approach to the search and extraction of
3347:"the further exploits of AARON, Painter"
3301:Association for Computational Creativity
3283:Association for Computational Creativity
2272:Bringsjord, S., Ferrucci, D. A. (2000),
1164:ICCC 2019, Charlotte, North Carolina, US
1094:: vague phrasing that often accompanies
2951:. IEEE Computer Society. pp. 1–9.
1470:The Creative Mind: Myths and Mechanisms
1325:
1257:Applications of artificial intelligence
743:Corpus of Contemporary American English
2770:Interaction with Machine Improvisation
2508:
2474:
2430:
2390:
2319:
2279:
2119:
2090:Lakoff, George; Johnson, Mark (2008),
2053:
2020:
1790:
1443:
741:have also shown to be possible. Using
652:Analogical Retrieval Constraint System
3415:Philosophy of artificial intelligence
2808:Dubnov, Shlomo; Surges, Greg (2014),
2689:Computer Models of Musical Creativity
2159:
2157:
2148:Applications of Cognitive Linguistics
2132:Special issue on Conceptual Blending.
1920:
1918:
1810:
1808:
1071:Criticism of computational creativity
7:
3333:An Overview of Artificial Creativity
2915:"Why I Think Mechanic Miner Is Cool"
648:Analogical Constraint Mapping Engine
276:merely to the agent that produces it
126:strand of work informing the other.
3044:Culpan, Daniel (1 September 2015).
1472:, London: Weidenfeld & Nicolson
1401:The social psychology of creativity
1379:"What is Computational Creativity?"
397:is a gallery with living exhibits")
3018:McFarland, Matt (31 August 2015).
2142:Pereira, Francisco Câmara (2006),
1748:Journal of Knowledge Based Systems
1315:Outline of artificial intelligence
270:Important categories of creativity
25:
3003:. Google Research. Archived from
2984:. Google Research. Archived from
2378:Veale, Tony, Hao, Yanfen (2007),
992:In August 2015, researchers from
825:Music and artificial intelligence
1438:The process of creative thinking
1377:Anna Jordanous (10 April 2014).
1344:. Series on Cultural Computing.
1079:
262:Key concepts from the literature
1695:Nguyen, D.; Widrow, B. (1989).
1403:, New York, NY: Springer-Verlag
1170:ICCC 2017, Atlanta, Georgia, US
1033:, this research area is called
607:"Felt like a tiger-fur blanket.
577:Hypothesis of creative patterns
3247:Algorithmic information theory
2850:, W.H. Freeman & Co., Ltd.
2150:, Amsterdam: Mouton de Gruyter
1991:Margaret Boden (10 May 2010).
1889:Thinking Skills and Creativity
1733:Computer models of creativity.
898:Visual and artistic creativity
894:raises problems of copyright.
888:song). The patented invention
629:" and "snake" are suggested).
48:generative adversarial network
1:
3405:Computational fields of study
2094:, University of Chicago press
1310:List of emerging technologies
1017:Creativity in problem solving
504:that employs ideas both from
2897:"Introducing Mechanic Miner"
2739:– via www.youtube.com.
1065:general theory of creativity
985:, thus creating a dreamlike
370:, with robot cowboys, as in
46:, an artwork generated by a
3222:10.1007/978-3-642-31140-6_1
1840:Computers in Human Behavior
1167:ICCC 2018, Salamanca, Spain
670:approach to the solving of
571:natural language generation
297:transformational creativity
27:Multidisciplinary endeavour
3431:
3251:Cambridge University Press
2691:, Cambridge, MA: MIT Press
2458:Pragmatics & Cognition
2361:Computational Intelligence
2220:10.4324/9780203856949.ch22
1106:Such statements should be
1063:unrealistic to speak of a
818:
753:and slang words using the
681:
450:
333:general-purpose technology
239:artificial neural networks
29:
2967:10.1109/CVPR.2015.7298594
2075:Koestler, Arthur (1964),
1901:10.1016/j.tsc.2016.05.009
1853:10.1016/j.chb.2017.04.035
1354:10.1007/978-3-031-53865-0
1292:Musikalisches WĂĽrfelspiel
860:London Symphony Orchestra
785:I need it for my dreams.
303:Generation and evaluation
1731:Boden, Margaret (1999),
1576:10.1109/TAI.2021.3100456
1468:Boden, Margaret (1990),
1399:Amabile, Teresa (1983),
1173:ICCC 2016, Paris, France
1035:creative problem solving
829:Computer-generated music
644:structure mapping engine
376:, or the reverse, as in
339:Combinatorial creativity
228:An image generated by a
54:Computational creativity
30:Not to be confused with
2421:Artificial Intelligence
2164:Carter, Ronald (2004).
1964:Harvard Business Review
1414:Minsky, Marvin (1967),
1252:Algorithmic composition
1051:artificial intelligence
949:constraint satisfaction
599:Example of a metaphor:
360:The Beverly Hillbillies
111:capable of human-level
74:artificial intelligence
3245:Chaitin, G.J. (1987).
2622:Gervás, Pablo (2001),
2341:Martin, James (1990),
2242:Meehan, James (1981),
1608:Computer Music Journal
1516:Computer Music Journal
1242:Artificial imagination
787:
293:exploratory creativity
233:
50:
3410:Creativity techniques
2725:on February 26, 2010.
2719:www.miller-mccune.com
2644:ACM Computing Surveys
2593:10.1515/ling.2004.021
2558:10.3366/cor.2019.0167
2257:Turner, S.R. (1994),
2110:Cognitive Linguistics
2077:{The act of creation}
1497:Gibson, P. M. (1991)
1298:Procedural generation
1272:Digital morphogenesis
939:system. Nonetheless,
819:Further information:
771:speech-error blends.
617:", "as pleasant as a
605:Example of a simile:
517:Linguistic creativity
227:
94:computational culture
62:mechanical creativity
58:artificial creativity
40:
18:Artificial creativity
3400:Cognitive psychology
3169:Psychological Review
2831:Science et Vie Micro
2687:Cope, David (2006),
2470:10.1075/pc.5.2.06bin
2168:. London: Routledge.
2092:Metaphors we live by
1683:Decision and Control
1108:clarified or removed
801:case-based reasoning
471:conceptual metaphors
78:cognitive psychology
70:creative computation
3342:on Think Artificial
2921:. 16 November 2012.
2825:Article de presse:
2797:. 22 December 2009.
2778:2010tsos.book..219A
2715:"miller-mccune.com"
2191:on February 8, 2018
2185:Oxford Dictionaries
1294:(Musical dice game)
684:Computational humor
595:Metaphor and simile
453:Conceptual blending
447:Conceptual blending
280:by society at large
230:text-to-image model
3352:2008-04-19 at the
3338:2008-03-25 at the
2903:. 5 November 2012.
1425:, pp. 120–125
1282:Generative systems
1267:Creative computing
919:Neuro-Evolutionary
815:Musical creativity
656:Douglas Hofstadter
510:genetic algorithms
437:Genetic algorithms
295:and the latter as
234:
214:genetic algorithms
137:Theoretical issues
66:creative computing
51:
32:Creative computing
3231:978-3-642-31139-0
3131:978-3-319-28078-3
2919:Games By Angelina
2901:Games By Angelina
2844:McCorduck, Pamela
2737:"Iamus' debut CD"
2044:Cognitive Science
1719:Cognitive Science
1363:978-3-031-53864-3
1159:COVID-19 pandemic
1152:COVID-19 pandemic
1125:
1124:
1031:cognitive science
994:TĂĽbingen, Germany
941:The Painting Fool
937:computational art
927:The Painting Fool
735:corpus linguistic
726:"). It then uses
704:portmanteau words
601:"She was an ape."
435:representations.
252:Michael I. Jordan
90:computational art
16:(Redirected from
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2721:. Archived from
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2187:. Archived from
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2018:
2015:The Way We Think
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1083:
1082:
1075:
935:creativity in a
885:René-Louis Baron
846:. Most notably,
794:
768:Stefan Th. Gries
668:machine learning
586:Story generation
406:Swiss Army knife
246:, D. Nguyen and
186:new, surprising,
43:Edmond de Belamy
21:
3430:
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3354:Wayback Machine
3340:Wayback Machine
3329:
3327:Further reading
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3182:10.1.1.405.2245
3175:(3): 994–1024.
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3024:Washington Post
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1340:, eds. (2024).
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1247:Algorithmic art
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1115:
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1023:problem solving
1019:
930:, developed by
900:
864:Iamus' debut CD
831:
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777:
716:Knowledge (XXG)
700:
686:
680:
678:Joke generation
635:
597:
588:
579:
519:
461:'s ideas about
459:Arthur Koestler
455:
449:
441:neural networks
341:
323:
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288:
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256:David Rumelhart
222:
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131:media synthesis
103:To construct a
56:(also known as
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3361:External links
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966:In July 2015,
899:
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891:Medal-Composer
821:Computer music
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755:hapax legomena
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2874:9783540728764
2870:
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2848:Aaron's Code.
2845:
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2755:New Scientist
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2229:9780203856949
2225:
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2214:, Routledge,
2213:
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2068:
2063:
2057:
2050:(2): 133–187.
2049:
2045:
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2030:
2024:
2017:, Basic Books
2016:
2009:
2006:
1994:
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1827:
1823:(2): 628–639.
1822:
1818:
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1800:
1794:
1787:
1784:, Cambridge:
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1116:December 2018
1109:
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1088:This article
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869:New Scientist
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790:Racter, from
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708:Lewis Carroll
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664:Keith Holyoak
661:
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640:Dedre Gentner
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493:
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486:
485:generic space
482:
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467:mental spaces
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326:for creating
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33:
19:
3381:In Its Image
3309:
3300:
3291:
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3240:
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3207:
3172:
3168:
3162:
3149:
3140:
3117:
3111:
3090:
3078:. Retrieved
3074:
3065:
3053:. Retrieved
3049:
3039:
3027:. Retrieved
3023:
3013:
3005:the original
2994:
2986:the original
2975:
2948:
2942:
2927:
2918:
2909:
2900:
2891:
2882:
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2838:
2830:
2818:
2809:
2803:
2794:
2785:
2769:
2763:
2754:
2745:
2731:
2723:the original
2718:
2709:
2697:
2688:
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2584:
2580:
2574:
2549:
2545:
2539:
2531:
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2498:
2491:
2461:
2457:
2447:
2433:cite journal
2424:
2420:
2407:
2380:
2373:
2364:
2360:
2354:
2342:
2336:
2322:cite journal
2313:
2309:
2296:
2273:
2267:
2258:
2252:
2243:
2237:
2211:
2205:
2193:. Retrieved
2189:the original
2184:
2174:
2165:
2147:
2137:
2122:cite journal
2113:
2109:
2091:
2085:
2076:
2070:
2056:cite journal
2047:
2043:
2037:
2014:
2008:
1996:. Retrieved
1986:
1975:. Retrieved
1963:
1954:
1933:
1925:
1892:
1888:
1878:
1843:
1839:
1829:
1820:
1816:
1777:
1770:
1751:
1747:
1741:
1732:
1726:
1718:
1712:
1703:
1690:
1682:
1676:
1668:
1662:
1653:
1644:
1614:(4): 44–53.
1611:
1607:
1601:
1566:
1562:
1552:
1522:(4): 27–43.
1519:
1515:
1493:
1484:
1478:
1469:
1437:
1431:
1422:
1409:
1400:
1394:
1382:. Retrieved
1372:
1341:
1334:Giannini, T.
1328:
1262:Computer art
1233:
1218:
1194:
1139:
1130:
1126:
1113:
1100:unverifiable
1092:weasel words
1089:
1064:
1061:
1020:
1011:
991:
971:
965:
958:
954:
940:
936:
932:Simon Colton
925:
924:
916:
908:Harold Cohen
901:
889:
882:
878:
867:
853:
832:
797:
791:
788:
780:
765:
751:portmanteaus
732:
701:
687:
660:Paul Thagard
650:) and ARCS (
636:
627:stick-insect
625:", "rope", "
615:bowling ball
611:Yorick Wilks
606:
604:
600:
598:
589:
580:
520:
502:
498:
491:
484:
456:
433:
428:Marlboro Man
414:mobile phone
386:poems, etc.)
377:
371:
358:
352:
342:
324:
315:
306:
296:
292:
289:
279:
275:
273:
265:
235:
210:
205:
201:
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194:
189:
185:
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164:
156:
151:
144:Ada Lovelace
140:
128:
124:
98:
93:
89:
69:
65:
61:
57:
53:
52:
41:
3385:Archive.org
3376:Archive.org
3345:Cohen, H.,
3297:"ICCC 2019"
3279:"ICCC 2020"
3150:youtube.com
3080:3 September
3055:3 September
3029:3 September
2823:(in French)
2650:(5): 1–30.
2581:Linguistics
2427:(41): 1–63.
1895:: 109–122.
1846:: 139–151.
1338:Bowen, J.P.
1238:(1st novel)
1102:information
987:psychedelic
978:open source
961:video games
506:symbolic AI
492:blend space
421:Emo Philips
408:; adding a
382:; Japanese
312:Co-creation
244:Paul Werbos
92:as part of
3394:Categories
3314:CCSMC 2016
3102:1508.06576
3075:gitxiv.com
2702:David Cope
2657:1812.04832
2367:: 520–552.
2316:: 119–139.
2195:January 4,
1977:2023-06-20
1945:1906.10188
1321:References
1235:1 the Road
1043:incubation
1027:psychology
983:pareidolia
904:visual art
848:David Cope
762:House M.D.
728:Web search
724:chrononaut
619:root canal
567:word-forms
559:witticisms
527:neologisms
463:creativity
328:innovation
321:Innovation
198:individual
113:creativity
82:philosophy
3318:WordPress
3177:CiteSeerX
2958:1409.4842
2932:deepdream
2601:0024-3949
2566:201903734
2244:TALE-SPIN
1998:7 January
1972:0017-8012
1909:1871-1871
1862:0747-5632
1786:MIT Press
1756:CiteSeerX
1593:238941032
1585:2691-4581
1384:7 January
1090:contains
973:DeepDream
970:released
747:neologism
739:neologism
712:headwords
706:" (after
698:Neologism
555:analogies
551:metaphors
535:allusions
373:Westworld
368:Wild West
3350:Archived
3336:Archived
3199:20658861
3122:Springer
3050:Wired UK
2846:(1991),
2674:54475410
2511:citation
2477:citation
2393:citation
2282:citation
2023:citation
1870:38485202
1793:citation
1704:IJCNN'89
1636:19286486
1544:36726968
1487:, Prager
1446:citation
1346:Springer
1228:See also
1003:Van Gogh
874:Melomics
866:, which
805:Metrical
759:TV drama
354:Fountain
190:valuable
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