Computational creativity (also known as artificial creativity, mechanical creativity or creative computation) is a multidisciplinary endeavour that is located at the intersection of the fields of artificial intelligence Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. Textbooks define the field as "the study and design of intelligent agents," where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who, cognitive psychology Cognitive psychology is a discipline within psychology that investigates the internal mental processes of thought such as visual processing, memory, thinking, learning, feeling, problem solving, and language, philosophy Philosophy is the study of general and fundamental problems concerning matters such as existence, knowledge, values, reason, mind, and language. It is distinguished from other ways of addressing fundamental questions by its critical, generally systematic approach and its reliance on rational argument. The word "philosophy" comes from the, and the arts.

The goal of computational creativity is to model, simulate or replicate creativity using a computer, to achieve one of several ends:

• to construct a program A computer program is a sequence of instructions written to perform a specified task for a computer. A computer requires programs to function, typically executing the program's instructions in a central processor. The program has an executable form that the computer can use directly to execute the instructions. The same program in its human- or computer A computer is a programmable machine that receives input, stores and manipulates data//information, and provides output in a useful format capable of human-level creativity Creativity is the ability to generate innovative ideas and manifest them from thought into reality. The process involves original thinking and then producing
• to better understand human creativity and to formulate an algorithmic perspective on creative behavior in humans
• to design programs that can enhance human creativity without necessarily being creative themselves

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 strand of work informing the other.

Theoretical issues

As measured by the amount of activity in the field (e.g., publications, conferences and workshops), computational creativity is a growing area of research. But the field is still hampered by a number of fundamental problems:

• Creativity is very difficult, perhaps even impossible, to define in objective terms.
• Creativity takes many forms in human activity, some eminent (meaning "recognized" or "ingenious", e.g., Einstein Albert Einstein (pronounced /ˈælbərt ˈaɪnstaɪn/; German: [ˈalbɐt ˈaɪnʃtaɪn] ; 14 March 1879 – 18 April 1955) was a theoretical physicist, philosopher and author who is widely regarded as one of the most influential and best known scientists and intellectuals of all time. A German-Swiss Nobel laureate, he is often regarded as the's creativity; sometimes referred to as "Creativity" with a capital C) and some mundane.
• Creativity can mean different things in different contexts: Is it a state of mind, a talent or ability, or a process? Does it describe a person, an activity or an end-product? Can collaborative work in which exceptional products emerge from simple interactions be considered creative?

These are problems that complicate the study of creativity in general, but certain problems attach themselves specifically to computational creativity:

• Can creativity be hard-wired? In existing systems to which creativity is attributed, is the creativity that of the system or that of the system's programmer or designer?
• How do we evaluate computational creativity? What counts as creativity in a computational system? Are natural language Natural Language processing is a field of computer science and linguistics concerned with the interactions between computers and human (natural) languages. Natural language generation systems convert information from computer databases into readable human language. Natural language understanding systems convert samples of human language into more generation systems creative? Are machine translation Machine translation, sometimes referred to by the abbreviation MT, is a sub-field of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another. At its basic level, MT performs simple substitution of words in one natural language for words in another. Using corpus systems creative? What distinguishes research in computational creativity from research in artificial intelligence Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. Textbooks define the field as "the study and design of intelligent agents," where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who generally?
• If eminent creativity is about rule-breaking or the disavowal of convention, how is it possible for an algorithmic system to be creative? In essence, this is a variant of the Ada Lovelace Augusta Ada King, Countess of Lovelace , born Augusta Ada Byron, was an English writer chiefly known for her work on Charles Babbage's early mechanical general-purpose computer, the analytical engine. Her notes on the engine include what is recognised as the first algorithm intended to be processed by a machine; as such she is regarded as the objection to machine intelligence, as recapitulated by modern theorists such as Teresa Amabile:^[1] If a machine can do only what it was programmed to do, how can its behavior ever be called creative?

Defining creativity in computational terms

Since no single perspective or definition seems to offer a complete picture of creativity, the AI researchers Newell, Shaw and Simon ^[2]developed the combination of novelty and usefulness into the corner-stone of a multi-pronged view of creativity, one that uses the following four criteria to categorize a given answer or solution as creative:

1. The answer is novel and useful (either for the individual or for society)
2. The answer demands that we reject ideas we had previously accepted
3. The answer results from intense motivation and persistence
4. The answer comes from clarifying a problem that was originally vague

Notice how these criteria touch on many of the stereotypical themes that are typically associated with creativity: newness and value (1), transformation and revolution (2), passion and drive (3), vision and insight (4). These four criteria also combine elements of the producer-perspective and the product-perspective described earlier: criterion (1) characterizes the two most important qualities of a creative product, while criteria (2) – (4) characterize the attitude and actions of the producer of such a product. A given product may satisfy all or none of these criteria, but we should expect products that exhibit all four to be widely perceived as creative, while products that exhibit just some of these criteria will be judged with greater subjectivity and variation. Though no criterion is likely to be either necessary or sufficient, criterion (1) is perhaps the most common hallmark of creativity and thus serves to anchor the others. From a computational perspective, then, one can consider (1) to be a must-have feature, and (2) – (4) as desirable extras.

Newell and Simon^[3][4] are best known for their contribution to the search-in-a-state-space paradigm of AI, sometimes caricatured as Good Old Fashioned AI (GOFAI In artificial intelligence research, GOFAI is an ironic derogative description of the oldest original approach to achieving artificial intelligence, based on logic and problem solving in severely restricted problem domains, for example chess playing. In the robotics research, the term is extended as GOFAIR ("Good Old Fashioned Artificial), and it is interesting to consider how the GOFAI paradigm can incorporate these criteria. From a search perspective, criterion (1) characterizes the goal or end-state of a computational search, criterion (4) characterizes the starting state from which the search is launched, criterion (3) characterizes the scale of the search, suggesting that many dead-ends are likely to be encountered, while criterion (2) suggests that well-worn pathways through the search space are best avoided if a creative end-state is to be reached.

Key ideas

Some high-level and philosophical themes recur throughout the field of computational creativity.^{[clarification needed]}

P-creativity and H-creativity

Margaret Boden^[5][6] refers to creativity that is novel merely to the agent that produces it as "P-creativity" (or "psychological creativity"), and refers to creativity that is recognized as novel by society at large as "H-creativity" (or "historical creativity").

Exploratory and transformational creativity

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 "exploratory creativity" and the latter as "transformational creativity", seeing the latter as a form of creativity far more radical, challenging, and rarer than the former. Following Newell and Simon’s criteria, 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 the subject of formalization, most notably in the work by Geraint Wiggins^[7].

Generation and evaluation

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 already known to the system are filtered at this stage. This body of potentially creative constructs are 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^[8], which is a psychological model of creative generation based on empirical observation of human creativity.

Combinatorial creativity

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:

• placing a familiar object in an unfamiliar setting (e.g., Marcel Duchamp Marcel Duchamp was a French artist whose work is most often associated with the Dadaist and Surrealist movements. Duchamp's output influenced the development of post-World War I Western art. He advised modern art collectors, such as Peggy Guggenheim and other prominent figures, thereby helping to shape the tastes of Western art during this period's Fountain Fountain is a 1917 work by Marcel Duchamp. It is one of the pieces which he called readymades , because he made use of an already existing object—in this case a urinal, which he titled Fountain and signed "R. Mutt". The art show to which Duchamp submitted the piece stated that all works would be accepted, but Fountain was not actually) or an unfamiliar object in a familiar setting (e.g., a fish-out-of-water story such as The Beverly Hillbillies The Beverly Hillbillies is an American television sitcom. Panned by many entertainment critics of its time, it quickly became a ratings success for CBS. The series was about a hillbilly family transplanted to Beverly Hills, California after finding oil on their land. A Filmways production, the series aired on CBS from September 26, 1962 –)
• Blending two superficially different objects or genres (e.g., a sci-fi story set in the Wild West, with robot cowboys, as in Westworld Westworld is a 1973 science fiction / thriller film written and directed by novelist Michael Crichton and produced by Paul Lazarus III. It stars Yul Brynner as a lifelike robot in a futuristic Western-themed amusement park, and Richard Benjamin and James Brolin as customers who are attacked by the park's robots when they malfunction; Jewish haiku Haiku listen (help·info), plural haiku, is a form of Japanese poetry, consisting of 17 moras (or on), in three phrases of 5, 7, and 5 moras respectively. Although haiku are often stated to have 17 syllables, this is inaccurate as syllables and moras are not the same. Haiku typically contain a kigo (seasonal reference), and a kireji (cutting word) poems, etc.)
• Comparing a familiar object to a superficially unrelated and semantically distant concept (e.g., "Makeup is the Western burka"; "A zoo The term zoological garden refers to zoology, the study of animals, a term deriving from the Greek zōon and lógos (λóγος, "study"). The abbreviation "zoo" was first used of the London Zoological Gardens, which opened for scientific study in 1828 and to the public in 1847. The number of major animal collections open to is a gallery with living exhibits")
• Adding a new and unexpected feature to an existing concept (e.g., adding a scalpel A scalpel, or lancet, is a small and extremely sharp bladed instrument used for surgery, anatomical dissection, and various arts and crafts . Scalpels may be single-use disposable or re-usable, re-usable scalpels can have attached, resharpenable blades or, more commonly, non-attached, replaceable blades. Disposable scalpels usually have a plastic to a Swiss Army knife A Swiss Army knife is a type of multi-function pocket knife or multi-tool. It originated in Ibach Schwyz, Switzerland in 1897. The term "Swiss Army knife" is a registered trademark owned by Wenger S.A. and Victorinox A.G., longtime suppliers of knives to the Swiss Armed Forces. Generally speaking, a Swiss Army knife has a blade as well; adding a camera A camera phone is a mobile phone which is able to capture either still photographs or video. Since early in the 21st century the majority of cameras and of mobile phones in use are camera phones. Most camera phones are simpler than separate digital cameras. Their usual fixed focus lenses and smaller sensors limit their performance in poor lighting, to a mobile phone A mobile phone is an electronic device used for full duplex two-way radio telecommunications over a cellular network of base stations known as cell sites. Mobile phones differ from cordless telephones, which only offer telephone service within limited range through a single base station attached to a fixed land line, for example within a home or)
• Compressing two incongruous scenarios into the same narrative to get a joke (e.g., the Emo Philips joke “Women are always using me to advance their careers. Damned anthropologists!”)
• Using an iconic image from one domain in a domain for an unrelated or incongruous idea or product (e.g., using the Marlboro Man The Marlboro Man is a figure used in tobacco advertising campaign for Marlboro cigarettes. In the United States, where the campaign originated, it was used from 1954 to 1999. The Marlboro Man was first conceived by Leo Burnett in 1954. The image involves a rugged cowboy or cowboys, in nature with only a cigarette. The ads were originally conceived image to sell cars, or to advertise the dangers of smoking-related impotence).

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 representations. Genetic algorithms The genetic algorithm is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by and neural networks Traditionally, the term neural network had been used to refer to a network or circuit of biological neurons; the modern usage of the term often refers to artificial neural networks, which are composed of artificial neurons or nodes. Thus the term has two distinct usages: can be used to generate blended or crossover representations that capture a combination of different inputs.

Bisociation

Arthur Koestler Arthur Koestler CBE was an author of essays, novels and autobiographies. Koestler was born in Budapest but, apart from his early school years, was educated in Austria. His early career was in journalism. In 1931 he joined the Communist Party of Germany but, disillusioned, he resigned from it in 1938 and in 1940 published a devastating anti- proposes a very general model of creative combination in his 1964 book The Act of Creation,^[9] claiming that scientific discovery, art and humour are all linked by a common mechanism called "bisociation The Act of Creation is a 1964 book by Arthur Koestler. It is a study of the processes of creativity and imagination in which Koestler explains that humans are most creative when rational thought is abandoned during dreams and trances. Koestler affirms that all creatures have the capacity for creative activity, frequently suppressed by the". Koestler lacked a formal, computational vocabulary for describing bisociation, which he defined as a reconciliation of two orthogonal matrices of thought (conceptual structures, mental spaces).

Conceptual blending

Mark Turner and Gilles Fauconnier ^[10][11] propose a model called Conceptual Integration Networks that elaborates upon the ideas of Koestler by synthesizing ideas from Cognitive Linguistic research into mental spaces and conceptual metaphors. Their basic model defines an integration network as four connected spaces:

• A first input space (contains one conceptual structure or mental space)
• A second input space (to be blended with the first input)
• A generic space of stock conventions and image-schemas that allow the input spaces to be understood from an integrated perspective
• A blend space 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 inputs.

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 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.

Blending theory is an elaborate framework that provides a rich terminology for describing the products of creative thinking, from metaphors to jokes to neologisms to adverts. It is most typically applied retrospectively, to describe how a blended conceptual structure could have arisen from a particular pair of input structures. These conceptual structures are often good examples of human creativity, but blending theory is not a theory of creativity, nor – despite its authors’ claims – does it describe a mechanism for creativity. The theory lacks an explanation for how a creative individual chooses the input spaces that should be blended to generate a desired result.

Nonetheless, 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^[12]. More recently, Francisco Câmara Pereira^[13] presented an implementation of blending theory that employs ideas both from GOFAI In artificial intelligence research, GOFAI is an ironic derogative description of the oldest original approach to achieving artificial intelligence, based on logic and problem solving in severely restricted problem domains, for example chess playing. In the robotics research, the term is extended as GOFAIR ("Good Old Fashioned Artificial and from genetic algorithms A genetic algorithm is a search technique used in computing to find exact or approximate solutions to optimization and search problems. Genetic algorithms are categorized as global search heuristics. Genetic algorithms are a particular class of evolutionary algorithms (EA) that use techniques inspired by evolutionary biology such as inheritance, 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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