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Novel Recipe Generation: A Concrete Application of Computational Creativity Theory
Abstract
Computational creativity is a relatively new and promising sub-field of artificial intelligence. Recently, many theoretical frameworks have established important aspects of a creative system. To further validate and advance these theories, there is a need for additional concrete applications, especially in new areas. While principles from computational creativity have been applied to many domains, such as art, music, and linguistics, the area of culinary science remains largely unex-plored. We introduce PIERRE, a computational recipe engine that demonstrates creativity through the generation of novel recipes. This creativity is demonstrated by considering both novelty and quality, and is discussed in terms of the applica-ble theoretical components implemented. We also claim that further applications of theory are necessary in order to facil-itate the development of the field, and validate this claim by presenting novel concepts discovered during the development process of PIERRE.
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The dominating models of information processes have been based on symbolic representations of information and knowledge. During the last decades, a variety of non-symbolic models have been proposed as superior. The prime examples of models within the non-symbolic approach are neural networks. However, to a large extent they lack a higher-level theory of representation. In this paper, conceptual spaces are suggested as an appropriate framework for non- symbolic models. Conceptual spaces consist of a number of 'quality dimensions' that often are derived from perceptual mechanisms. It will be outlined how conceptual spaces can represent various kind of information and how they can be used to describe concept learning. The connections to prototype theory will also be presented.
WASP is a forward reasoning rule-based system that takes as input data a set of words and a set of verse patterns and returns a set of verses. Using a generate and test method, guided by a set of construction heuristics obtained from formal literature on Spanish poetry, the system can operate in two modes: either generating an unrestricted set of verses, or generating a poem according to one of three predefined structures (romance, cuarteto, or terceto). Five different construction heuristics are tested over different combinations of two sets of initial data, one obtained from a classic poem and one obtained from a paragraph of a doctoral thesis in linguistics. A set of numerical parameters are extracted from each test, and evaluated in search of significant correlations. The aim is to ascertain the relative importance of size of initial vocabulary, choice of words, choice of verse patterns and construction heuristics with respect to the general acceptability of the resulting verse.
We combine a machine vision system that recognises emotions and a non-photorealistic rendering (NPR) system to automatically pro- duce portraits which heighten the emotion of the sitter. To do this, the vision system analyses a short video clip of a person express- ing an emotion, then tracks the movement of facial features and uses this tracking data to analyse which emotion was expressed and what the temporal dynamics of the expression were. The im- age where the emotion is expressed strongest, the location of the facial features in that image and a keyword describing the emotion detected are passed to the NPR software. This keyword is used to choose appropriate (simulated) art materials, colour palettes, ab- straction methods and painting styles, so that the rendered image may heighten the emotion being expressed. We describe the vision and rendering systems and their combination, and provide exam- ples of portraits produced in this emotionally aware fashion.
The greatest rhetorical challenge to developers of creative artificial intelligence systems is convincingly arguing that their
software is more than just an extension of their own creativity. This paper suggests that “creative autonomy,” which exists
when a system not only evaluates creations on its own, but also changes its standards without explicit direction, is a necessary
condition for making this argument. Rather than requiring that the system be hermetically sealed to avoid perceptions of human
influence, developing creative autonomy is argued to be more plausible if the system is intimately embedded in a broader society
of other creators and critics. Ideas are presented for constructing systems that might be able to achieve creative autonomy.
Creativity isn't magical. It's an aspect of normal human intelligence, not a special faculty granted to a tiny elite. There are three forms: combinational, exploratory, and transformational. All three can be modeled by AI - in some cases, with impressive results. AI techniques underlie various types of computer art. Whether computers could "really" be creative isn't a scientific question but a philosophical one, to which there's no clear answer. But we do have the beginnings of a scientific understanding of creativity. Copyright © 2009, Association for the Advancement of Artificial Intelligence. All rights reserved.
I have a very creative family; a fourteen-year-old who draws with unusual skill and has been playing the piano since she was six, a twelve year old who is equally at home in drawing, painting, sculpture and mathematics, and Zana, my three year-old daughter, who speaks two languages and has been drawing like a five-year-old since she was two-and-a-half. The mother of these three is a distinguished Japanese poet and writer. As for the only male in this feminist stronghold, I've been making my life and my living in art for fifty years, for about thirty of which I've been writing computer programs of sufficient ... something ... to explain why I'm writing this paper. Which brings me to the last member of the household. When I don't keep it busy with email, designing machines, writing conference papers and doing my tax returns, AARON is sitting quietly on my desk, generating original images at the rate of about one every two minutes (fig I). And, most particularly when I'm watching it, I am aware of a couple of questions that need to be addressed: if I say that I have a creative family, and then I were to say that I have a creative computer program, would I mean the same thing by the word "creative"? And how far could I justify the claim that my computer program -or any other computer program -is, in fact, creative? I'd try to address those questions if I knew what the word "creative" meant: or if I thought I knew what anyone else meant by it.
Riddles based on simple puns can be classified according to the patterns of word, syllable or phrase similarity they depend upon. We have devised a formal model of the semantic and syntactic regularities underlying some of the simpler types of punning riddle. We have also implemented this preliminary theory in a computer program which can generate riddles from a lexicon containing general data about words and phrases; that is, the lexicon content is not customized to produce jokes. An informal, formative evaluation of the program's results by a set of human judges suggests that the riddles produced by this program are of comparable quality to those in general circulation among school children.
In recent years, Artificial Intelligence researchers have largely focused their efforts on solving specific problems, with less emphasis on 'the big picture' - automating large scale tasks which require human-level intelligence to undertake. The subject of this book, automated theory formation in mathematics, is such a large scale task. Automated theory formation requires the invention of new concepts, the calculating of examples, the making of conjectures and the proving of theorems. This book, representing four years of PhD work by Dr. Simon Colton demonstrates how theory formation can be automated. Building on over 20 years of research into constructing an automated mathematician carried out in Professor Alan Bundy's mathematical reasoning group in Edinburgh, Dr. Colton has implemented the HR system as a solution to the problem of forming theories by computer. HR uses various pieces of mathematical software, including automated theorem provers, model generators and databases, to build a theory from the bare minimum of information - the axioms of a domain. The main application of this work has been mathematical discovery, and HR has had many successes. In particular, it has invented 20 new types of number of sufficient interest to be accepted into the Encyclopaedia of Integer Sequences, a repository of over 60,000 sequences contributed by many (human) mathematicians.
I summarise and attempt to clarify some concepts presented in and arising from Margaret Boden’s (1990) descriptive hierarchy of creativity, by beginning to formalise the ideas she proposes. The aim is to move towards a model which allows detailed comparison, and hence better understanding, of systems which exhibit behaviour which would be called “creative” in humans. The work paves the way for the description of naturalistic, multi-agent creative AI systems, which create in a societal context.I demonstrate some simple reasoning about creative behaviour based on the new framework, to show how it might be useful for the analysis and study of creative systems. In particular, I identify some crucial properties of creative systems, in terms of the framework components, some of which may usefully be proven a priori of a given system.I suggest that Boden’s descriptive framework, once elaborated in detail, is more uniform and more powerful than it first appears.
Adaptive documents undergo many transformations during their generation, including insertion and deletion of content. One major problem in this scenario is the preservation of the aesthetic qualities of the document during those transformations.As adaptive documents are instances of a template, the aesthetic quality of an instance with respect to the template could be evaluated by aesthetic measures providing scores to any desired quality parameters. These parameters measure the deviation of the instance from the desired template. This evaluation could assure the quality of instances during their generation and final output.This paper introduces the use of document templates to support aesthetic measures of document instances. A score is assigned to a document instance according to the differences detected from the original template. Considering the original template as an ideal result, the quality of a document instance will decrease according to the number and severity of the changes applied to produce it. So, documents that are below a given threshold can be sent for further (possibly human) review, and any others are accepted.The amount of change with respect to the template will reflect the document quality, and in such a model the quality of instances can be considered as a distance from that original.
We add to the discussion of how to assess the creativ- ity of programs which generate artefacts such as poems, theorems, paintings, melodies, etc. To do so, we first review some existing frameworks for assessing artefact generation programs. Then, drawing on our experience of building both a mathematical discovery system and an automated painter, we argue that it is not appro- priate to base the assessment of a system on its output alone, and that the way it produces artefacts also needs to be taken into account. We suggest a simple frame- work within which the behaviour of a program can be categorised and described which may add to the per- ception of creativity in the system.
Over recent decades there has been a growing interest in the question of whether computer programs are capable of genuinely creative activity. Although this notion can be explored as a purely philosophical debate, an alternative perspective is to consider what aspects of the behaviour of a program might be noted or measured in order to arrive at an empirically supported judgement that creativity has occurred. We sketch out, in general abstract terms, what goes on when a potentially creative program is constructed and run, and list some of the relationships (for example, between input and output) which might contribute to a decision about creativity. Specifically, we list a number of criteria which might indicate interesting properties of a program’s behaviour, from the perspective of possible creativity. We go on to review some ways in which these criteria have been applied to actual implementations, and some possible improvements to this way of assessing creativity.
Creativity is sometimes taken to be an inexplicable aspect of human activity. By summarizing a considerable body of literature on creativity, I hope to show how to turn some of the best ideas about creativity into programs that are demonstrably more creative than any we have seen to date. I believe the key to building more creative programs is to give them the ability to reflect on and modify their own frameworks and criteria. That is, I believe that the key to creativity is at the metalevel.
Our species cannot survive without humor and future human-machine interaction systems will be required to handle humor. From a practical point of view, humor is an important resource for getting selective attention, help in memorizing names and situations, etc. Even if deep modeling of humor in all of its facets is not something available in the near future, there is something concrete that has been achieved and that can help in providing attention to the field. The paper refers to the results of HAHACRONYM, a project devoted to humorous acronym production, a circumscribed task that nonetheless requires various generic components. The project opens the way to developments for creative language. Electronic commerce, for instance, will include flexible and individual-oriented humorous promotion more or less as it happened in the world of broadcasted advertisement.
esis, and this is the book of the program. Here is a sample from one of Minstrel's stories (p. 72): It was the spring of 1089, and a knight named Lancelot returned to Camelot from elsewhere. Lancelot was hot tempered. Once, Lancelot lost a joust. Because he was hot tempered, Lancelot wanted to destroy his sword. Lancelot struck his sword. His sword was destroyed. One day, a Lady of the court named Andrea wanted to have some berries. Andrea went to the woods. Andrea had some berries cause Andrea picked some berries. At the same time, Lancelot's horse moved Lancelot to the woods. This unexpectedly caused him to be near Andrea. Because Lancelot was near Andrea, Lancelot saw drea. Lancelot loved Andrea. This is about 40% of the story. We human readers are meant to infer that Lancelot fell in love with Andrea. It's not a bad story. In the next paragraph Lancelot is again moved by his horse, unexpectedly, into the woods, and he sees Andrea kissing someone called Frederick. His ho
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