Computational Creativity Evaluation

Creativity and diversity are key components of success in idea generation, but each includes many dimensions. Paradigm-relatedness is an indicator of the style of creativity and diversity that has been overlooked often in assessing ideation. The goals for this study were to synthesize the literature on paradigm-relatedness, and develop and test alternative approaches for operationalizing paradigm-relatedness in ideation. The synthesis of the literature focused on reviewing both paradigm-relatedness theoretical frameworks and methodological approaches. Then, two alternative paradigm-relatedness metric approaches-category-based and componentbased-were developed. Finally, ideation data was collected and coded to evaluate the reliability, ease of use, and potential applications of each approach. The category-based approach was a more reliable and faster way to code paradigm-relatedness, and so it may be more suited for research or evaluation at scale. In contrast, the component-based approach provided more explicit information on all aspects of paradigm-relatedness, but was more challenging to code reliably and more time-consuming. The component-based approach may be more suited to guiding smaller teams or individual designers in achieving paradigm-relatedness creativity and diversity. Neither approach was found to be universally ideal, and so consideration of the trade-offs is important in deciding which is most appropriate in a given situation.

Biomarkers are vital to detect diseases in various clinical stages. A variety of cancer serum biomarkers are already known, while for more accurate cancer-type detection, there required more rigorous evaluation manners, especially computational evaluation measures, for biomarkers. In this review, we first show three typical pitfalls in finding biomarkers and their examples, after briefly presenting standard five clinical biomarker screening phases by National Cancer Institute. We then introduce current computational biomarker evaluation measures, including current, standard methods with their intrinsic features. We further show an up-to-date list of existing cancer serum biomarkers, pointing out several issues, being caused by the limitations of current biomarker evaluation approaches. Finally we discuss the current attempts to develop new, statistically robust, computational serum-based biomarker measures in terms of specificity to each of various cancer types.

The development of AI has become a disruptive and transformative force that alters all forms of creative expression, including visual art, music, literature, and performance. Artistic content generation through AI technology expands authorship constraints by enabling machines to produce art in various ways, enhancing existing works, and executing simulations. This paper presents a comprehensive assessment of AI implementation across various art fields before examining how AI impacts human creative capabilities and identifying the ethical and conceptual issues that arise from machine-generated artworks. This paper synthesises contemporary research from 2019 to 2025 on AI technology in creative applications. The creative field currently experiences major changes because machine-produced artwork becomes more sophisticated thanks to AI tools, including DALL-E, Stable Diffusion, GPT-4 and AI-generated content. AI technology introduces new artistic territory but raises debates on copyright rules, sparks authorship debates, affects employment conditions and disrupts human-machine professional interactions. The investigation highlights both the benefits and challenges that arise from artificial intelligence applications in creativity. With AI tools, humans can enhance their artistic quality by leveraging AI as a collaborative tool and venture into new artistic domains that surpass human capabilities. Prior regulatory action must be taken urgently to address significant ethical concerns, including copyright conflicts, data bias, and the erosion of artistic authenticity. The review emphasizes the importance of integrating knowledge from artistic disciplines with both legal frameworks and ethical AI regulations to strike a balance between technological progress and artistic quality.

In this paper we introduce and discuss the apprentice framework, which we speculate can be used to plan and evaluate computational creativity projects. The framework defines a sequence of phases a system must follow in order to reach a level of creativity acceptable to a set of human judges. It also establishes four aspects of a creative piece susceptible of creative work. We mention some examples from different artistic disciplines. Our work focuses on establishing an environment as well as a team of people and machines to foster, study and monitor the emergence of creativity. On Human and Machine Creativity Assessing creativity in machines has become a prime issue in computational creativity after many systems have been built that exhibit a behavior that can intuitively be considered creative. The domains of such systems are so varied, and the versions of each one so many, that comparing them to one another or with different versions of themselves has become a hard task. Every sys...

The permutation flowshop problem is a classic machine scheduling problem where n jobs must be processed on a set of m machines disposed in series and where each job must visit all machines in the same order. Many production scheduling problems resemble flowshops and hence it has generated much interest and had a big impact in the field, resulting in literally hundreds of heuristic and metaheuristic methods over the last 60 years. However, most methods proposed for makesan minimisation are not properly compared with existing procedures so currently it is not possible to know which are the most efficient methods for the problem regarding the quality of the solutions obtained and the computational effort required. In this paper, we identify and exhaustively compare the best existing heuristics and metaheuristics so the state-of-the-art regarding approximate procedures for this relevant problem is established.

We present a proposal for meta-level evaluation in creative systems. In this paper, the Mexica creative system is the subject of our analysis. To achieve meta-level evaluation, we have constructed a program that interacts with Mexica’s inputs and its outputs. The meta-level system evaluates the results and makes decisions based on them. For decision-making it includes heuristics that are defined in terms of Mexica’s results; these are rules particular to the object-level system. We also include other general metrics that apply in any other creative system. For example, Ritchie’s criteria for evaluating creative systems are included in this proposal.

This chapter examines the field of algorithmic composition from the perspective of computational creativity. It begins by introducing the idea of computational creativity as a philosophical perspective. Next, it introduces a method for consideration of the properties of creative systems, the Creative Systems Framework (CSF; Wiggins, 2006a,b). The CSF becomes the starting point for a discussion of a system of comparison specific to algorithmic composition as an artistic and technical practice. Finally, the chapter sketches a road map for future developments in algorithmic composition and live coding, in these terms.

The research described in this work focuses on identifying key components for the task of irony detection. By means of analyzing a set of customer reviews, which are considered as ironic both in social and mass media, we try to find hints about how to deal with this task from a computational point of view. Our objective is to gather a set of discriminating elements to represent irony. In particular, the kind of irony expressed in such reviews. To this end, we built a freely available data set with ironic reviews collected from Amazon. Such reviews were posted on the basis of an online viral effect; i.e. contents whose effect triggers a chain reaction on people. The findings were assessed employing three classifiers. The results show interesting hints regarding the patterns and, especially, regarding the implications for sentiment analysis.

We start with a critical examination of the traditional view of creativity in which the creator is the major player. We analyze many different examples to point out that the origin of all different creativity scenarios is rooted in the viewer-artifact interaction. To recognize this explicitly, we propose an alternative formulation of creativity by putting the viewer in the driver's seat. We examine some implications of this formulation, especially for the role of computers in creativity, and argue that it captures the essence of creativity more accurately.

Nitro group containing furans such as dantrolene, a muscle relaxant and nitrofurantoin an antibiotic are in clinical use 1 while other derivatives find diverse applications in industry 2-4. Yet other substituted furan-2-carbaldehydes possess a C 2 cabonyl group that may act as a reactive centre for various condensation reactions. Many of the published condensations products are biologically active compounds 5,6 or can be used as intermediates in organic synthesis 7,8. Chalcones, α,β-unsaturated ketones 9-11 display a wide range of pharmaceutical properties, including cytotoxity 12, 13 , antimitotic 14 , antimutagenic 15 antitumor-promoting, antibacterial 16 , antiviral 17 and anti-inflammatory 18 activities. They are also useful in material science fields such as non-linear optics (NLO) 19 , optical limiting 20 , electrochemical sensing 21 , Langmuir films and photo-initiated polymerization 22. Various chalcone derivatives are notable materials for their second harmonic generation (SHG) 23. They are well known intermediates for synthesizing various heterocyclic compounds. Cyclization of chalcones, leading to various heterocycles, such as thiazines, pyrimidines, pyrazoline etc. which have potentials as efficacious antibacterial agents. A survey of literature in the recent past reveals that some pyrazoline derivatives possess antibacterial 24,25 , anti-inflammatory 26,27 and antifungal effects 28. Some 1-aryl-3-[5-(p-nitrophenyl)-2-propen-1-ones were obtained from the corresponding 5-p-nitrophenylfuran-2carbaldehyde are reported and were used for the synthesis of 1,2,4-triazolo[3,4-b]-1,3,4-thiadiazines claimed to have antibacterial and antiviral properties 29. We would now like to report

This study presents a new dataset on rumor detection in Finnish language news headlines. We have evaluated two different LSTM based models and two different BERT models, and have found very significant differences in the results. A fine-tuned FinBERT reaches the best overall accuracy of 94.3% and rumor label accuracy of 96.0% of the time. However, a model fine-tuned on Multilingual BERT reaches the best factual label accuracy of 97.2%. Our results suggest that the performance difference is due to a difference in the original training data. Furthermore, we find that a regular LSTM model works better than one trained with a pretrained word2vec model. These findings suggest that more work needs to be done for pretrained models in Finnish language as they have been trained on small and biased corpora.

In this paper we introduce and discuss the apprentice framework, which we speculate can be used to plan and evaluate computational creativity projects. The framework defines a sequence of phases a system must follow in order to reach a level of creativity acceptable to a set of human judges. It also establishes four aspects of a creative piece susceptible of creative work. We mention some examples from different artistic disciplines. Our work focuses on establishing an environment as well as a team of people and machines to foster, study and monitor the emergence of creativity. On Human and Machine Creativity Assessing creativity in machines has become a prime issue in computational creativity after many systems have been built that exhibit a behavior that can intuitively be considered creative. The domains of such systems are so varied, and the versions of each one so many, that comparing them to one another or with different versions of themselves has become a hard task. Every sys...

Chalcone (1,3-diphenylprop-2-en-1-one) compounds are of natural or synthetic origins and possess a diversity in bioactivities. Recently, the inhibitory activities of heterocyclic chalcones against different cancer cell lines have raised much concern. The study aimed at synthesizing some heterocyclic chalcones and determining their in vitro cytotoxicity on rhabdomyosarcoma (RD) cell line. Heterocyclic chalcones in this study were developed on the basis of the idea that heteroaryl moieties either on ring A or ring B of chalcones might provide cytotoxicity on cancer cells. These compounds were prepared by Claisen-Schmidt condensation the in vitro cytotoxicity of the compounds on rhabdomyosarcoma (RD) cell line has been evaluated using the microculture tetrazolium (MTT) assay. A total of synthesized heterocyclic chalcones has been synthesized and their structures were elucidated by spectrometric methods. Bioassay results revealed that 5 out of 20 compounds showed activities against RD cells with IC 50 values less than 20μM. The compound 7 possessing two heterocyclic moieties (phenothiazine as A ring and thiophene as B ring) was considered as the most potential with IC 50 at 12.51 μM (compare with taxol having IC 50 at 10.88μM). The results demonstrate that heterocyclic chalcones are promising compounds for developing anticancer drugs.

The field of computational creativity, including musical metacreation, strives to develop artificial systems that are capable of demonstrating creative behavior or producing creative artefacts. But the claim of creativity is often assessed, subjectively only on the part of the researcher, and not objectively at all. This paper provides theoretical motivation for more systematic evaluation of musical metacreation and computationally creative systems, and presents an overview of current methods used to assess human and machine creativity that may be adapted for this purpose. In order to highlight the need for a varied set of evaluation tools, a distinction is drawn between three types of creative systems: those which are purely generative; those which contain internal or external feedback; and those which are capable of reflection and self-reflection. To address the evaluation of each of these aspects, concrete examples of methods and techniques are suggested to help researchers 1) evaluate their systems' creative process and generated artefacts, and test their impact on the perceptual, cognitive, and affective states of the audience, and 2) build mechanisms for reflection into the creative system, including models of human perception and cognition, to endow creative systems with internal evaluative mechanisms to drive self-reflective processes. The first type of evaluation can be considered external to the creative system, and may be employed by the researcher to both better understand the efficacy of their system and its impact, and to incorporate feedback into the system. Here, we take the stance that understanding human creativity can lend insight to computational approaches, and knowledge of how humans perceive creative systems and their output can be incorporated into artificial agents as feedback to provide a sense of how a creation will impact the audience. The second type centers around internal evaluation, in which the system is able to reason about its own behavior and generated output. We argue that creative behavior cannot occur without feedback and reflection by the creative/metacreative system itself. More rigorous empirical testing will allow computational and metacreative systems to become more creative by definition, and can be used to demonstrate the impact and novelty of particular approaches.

The Remote Associates Test (RAT) is a test used for measuring creativity as relying on the power of making associations, and it normally takes a linguistic form (i.e., given three words, a fourth word associated with all three is asked for). The aim of this paper is towards generalizing this test to other domains, checking for its possible application in the visual domain (i.e., given three images, an object associated to them is asked for). A pilot visual version of the Remote Associates Test (RAT-V) was created and given to human participants. A previous solver of the compound linguistic Remote Associates Test (comRAT-C) was adapted to become a prototype which can solve the visual Remote Associates Test (comRAT-V).

Design fixation experiments often require participants to solve a design problem whilst being exposed to an example solution and instructions for how to treat that example. However, little is known about the influence of such instructions, leading to difficulties in interpreting results and understanding how the introduction of examples affects idea generation. In our experiment, participants were all provided with the same design problem and example solution, but were presented with different instructions, ranging from strongly encouraging copying the example to strongly discouraging copying. Analyses of participants' work indicated that only the instructions encouraging copying had an effect. When encouraged to copy, participants tended to only copy the structural features of the example rather than the underlying concept. By contrast, the number of features copied was not reduced when participants were discouraged from copying. These findings suggest that there are subtle interactions between instructions and stimuli that influence design fixation.

The multiplicity of the fields that fall under the umbrella of Musical Metacreation are many, as noted by the associate editors of this first of two special issues on the topic. The editors introduce the papers and the authors presented in this issue and explore how their work helps to provide machines with musical abilities.

Having in mind the lack of work on the automatic recognition of verbal humour in Portuguese, a topic connected with fluency in a natural language, we describe the creation of three corpora, covering two styles of humour and four sources of non-humorous text, that may be used for related studies. We then report on some experiments where the created corpora were used for training and testing computational models that exploit content and linguistic features for humour recognition. The obtained results helped us taking some conclusions about this challenge and may be seen as baselines for those willing to tackle it in the future, using the same corpora.

Musical duets are a type of creative partnership with a long history of artistic practice. What can they tell us about creative partnerships between a human and a computer? To explore this question, we implemented an activity-based model of duet interaction in software designed to support musical metacreation and investigated the experience of performing with it. The activity-based model allowed for the application of reflexive interactive processes, previously used in dialogic interaction, to a synchronous musical performance context. The experience of improvising with the computational agent was evaluated by expert musicians, who reported that interactions were fun, engaging, and challenging, despite some obvious limitations in the musical sophistication of the software. These findings reinforce the idea that even simple metacreative systems can stimulate creative partnerships and, further, that creative human-machine duet partnerships may well produce, like human-human duet partn...

Fixation is one of the major obstacles that individuals face in creative idea generation contexts. Several studies have shown that individuals unintentionally tend to fixate to the examples they are shown in a creative ideation task, even when instructed to avoid them. Most of these studies used examples formulated with high level of specificity. However, no study has examined individuals' creative performance under an instruction to diverge from given examples, when these examples are formulated with a high level of abstraction. In the present study, we show that (a) instructing participants to avoid using common examples when formulated with a high level of specificity increases fixation; whereas (b) instructing participants to avoid such examples while using a more abstract level for stating these common examples-such as a categorization of these examples-mitigates fixation and doubles the number of creative ideas generated. These findings give new insights on the key role of categorization in creative ideation contexts.

Recently, many programs have been written to perform tasks which are usually regarded as requiring creativity in humans. We can derive some commonalities between these programs in order to build further creative programs. Key to this is the derivation of certain measures which assess how creative a program is. Starting from recent proposals by Ritchie, we define possible measures which describe the extent to which a program produces novel output. We discuss how this relates to the creativity of the program.

Generation alone does not make a Computational Creativity system. But, what about machines that only evaluate? When it comes to co-creative systems, humans often take on the primary evaluative role, while machines assist with the generation of creative artifacts. In this paper, we propose flipping the paradigm, envisioning machines that (only) evaluate humans. Challenges and opportunities in this new direction are discussed.

Creativity and diversity are key components of success in idea generation, but each includes many dimensions. Paradigm-relatedness is an indicator of the style of creativity and diversity that has been overlooked often in assessing ideation. The goals for this study were to synthesize the literature on paradigm-relatedness, and develop and test alternative approaches for operationalizing paradigm-relatedness in ideation. The synthesis of the literature focused on reviewing both paradigm-relatedness theoretical frameworks and methodological approaches. Then, two alternative paradigm-relatedness metric approaches-category-based and componentbased-were developed. Finally, ideation data was collected and coded to evaluate the reliability, ease of use, and potential applications of each approach. The category-based approach was a more reliable and faster way to code paradigm-relatedness, and so it may be more suited for research or evaluation at scale. In contrast, the component-based approach provided more explicit information on all aspects of paradigm-relatedness, but was more challenging to code reliably and more time-consuming. The component-based approach may be more suited to guiding smaller teams or individual designers in achieving paradigm-relatedness creativity and diversity. Neither approach was found to be universally ideal, and so consideration of the trade-offs is important in deciding which is most appropriate in a given situation.

This is a call to action. The time is ripe for a creative turn in computing. This article sets out a vision of what Creative Computing is and what it might become. It distinguishes between Creative Computing and computational creativity, and then lays out a theoretical framework. It proposes that Creative Computing is mainly happening in software. It compares the process of software development with the process of artistic creation and looks at ways in which the two might productively overlap or merge. It considers the levels of abstraction required in both and interrogates both their semantics and underlying principles from a philosophical and practical point of view. Finally, it sets three types of new challenges for Creative Computing in terms of software.

This article will analyse the preconditions of sense of humour for artificial intelligence. Can artificial intelligence have a sense of humour? Is there a difference between human and machine laughter? Some machines already fulfil certain conditions which are associated with the human sense of humour: on the most superficial level machines appear to laugh and produce jokes, and they recognise sarcasm and punchlines, and they can evaluate funniness. In short, artificial intelligence is already able to recognise humour, and reacts to it accordingly. Furthermore, people laugh with humorous machines. However, it is still uncertain whether artificial intelligence can have a sense of humour or not, at least in comparison to a human sense of humour. To build bridges between AI research and philosophy of humour, this article proposes that there are (at least) five notable philosophical issues to be addressed if we are to accept that machines can have a (humanlike) sense of humour. These principles are: 1) worldview, 2) self- consciousness, 3) self-reflection, 4) self-criticism, and 5) losing control.

Recently, many programs have been written to perform tasks which are usually regarded as requiring creativity in humans. We can derive some commonalities between these programs in order to build further creative programs. Key to this is the derivation of certain measures which assess how creative a program is. Starting from recent proposals by Ritchie, we define possible measures which describe the extent to which a program produces novel output. We discuss how this relates to the creativity of the program.

Design fixation refers to designing under the influence of precedents with the inappropriate reuse of their features. With the aim of better understanding of design fixation and create a compendious framework, this paper reviewed 50 new empirical studies in this area. Design fixation studies are classified into (a) investigating conditions that affect design fixation occurrence, (b) proposing affordance sources, and (c) suggesting overcome instructions and methods. Results indicated that there exist eight key factors, namely designer, design problem, sources, design process, design outcome, designers' goal, distance between source and problem, and similarity between source and design outcome. Finally, a new framework was developed on the basis of the key factors and variables. By synthesizing the variables and the findings of these papers, future research directions are proposed.

In this paper, we provide a philosophical account of the value of creative systems for individuals and society. We characterize creativity in very broad philosophical terms, encompassing natural, existential, and social creative processes, such as natural evolution and entrepreneurship, and explain why creativity understood in this way is instrumental for advancing human well-being in the long term. We then explain why current mainstream AI tends to be anti-creative, which means that there are moral costs of employing this type of AI in human endeavors, although computational systems that involve creativity are on the rise. In conclusion, there is an argument for ethics to be more hospitable to creativity-enabling AI, which can also be in a trade-off with other values promoted in AI ethics, such as its explainability and accuracy.

Chalcone (1,3-diphenylprop-2-en-1-one) compounds are of natural or synthetic origins and possess a diversity in bioactivities. Recently, the inhibitory activities of heterocyclic chalcones against different cancer cell lines have raised much concern. The study aimed at synthesizing some heterocyclic chalcones and determining their in vitro cytotoxicity on rhabdomyosarcoma (RD) cell line. Heterocyclic chalcones in this study were developed on the basis of the idea that heteroaryl moieties either on ring A or ring B of chalcones might provide cytotoxicity on cancer cells. These compounds were prepared by Claisen-Schmidt condensation the in vitro cytotoxicity of the compounds on rhabdomyosarcoma (RD) cell line has been evaluated using the microculture tetrazolium (MTT) assay. A total of synthesized heterocyclic chalcones has been synthesized and their structures were elucidated by spectrometric methods. Bioassay results revealed that 5 out of 20 compounds showed activities against RD cells with IC 50 values less than 20μM. The compound 7 possessing two heterocyclic moieties (phenothiazine as A ring and thiophene as B ring) was considered as the most potential with IC 50 at 12.51 μM (compare with taxol having IC 50 at 10.88μM). The results demonstrate that heterocyclic chalcones are promising compounds for developing anticancer drugs.

We present a proposal for meta-level evaluation in creative systems. In this paper, the Mexica creative system is the subject of our analysis. To achieve meta-level evaluation, we have constructed a program that interacts with Mexica’s inputs and its outputs. The meta-level system evaluates the results and makes decisions based on them. For decision-making it includes heuristics that are defined in terms of Mexica’s results; these are rules particular to the object-level system. We also include other general metrics that apply in any other creative system. For example, Ritchie’s criteria for evaluating creative systems are included in this proposal.

In English,“puns” are usually perceived as a subclass of “jokes”. In Japanese, however, this is not necessarily true. In this paper we investigate whether Japanese native speakers perceive dajare (puns) as jooku (jokes). We first summarize existing research in the field of computational humor, both in English and Japanese, focusing on the usage of these two terms. This shows that in works of Japanese native speakers, puns are not commonly treated as jokes. Next we present some dictionary definitions of dajare and ...

We consider automated generation of humorous texts by substitution of a single word in a given short text. In this setting, several factors that potentially contribute to the funniness of texts can be integrated into a unified framework as constraints on the lexical substitution. We discuss three types of such constraints: formal constraints concerning the similarity of sounds or spellings between the original word and the substitute, semantic or connotational constraints requiring the substitute to be a taboo word, and contextual constraints concerning the position and context of the replacement. Empirical evidence from extensive user studies using real SMSs as the corpus indicates that taboo constraints are statistically very effective, and so is a constraint requiring that the substitution takes place at the end of the text even though the effect is smaller. The effects of individual constraints are largely cumulative. In addition, connotational taboo words and word position have...

One of the most amazing characteristics that defines the human being is humour. Its analysis implies a set of subjective and fuzzy factors, such as the linguistic, psychological or sociological variables that produce it. This is one of the reasons why its automatic processing seems to be not straightforward. However, recent researches in the Natural Language Processing area have shown that humour can automatically be generated and recognised with success. On the basis of those achievements, in this study we present the experiments we have carried out on a collection of Italian texts in order to investigate how to characterize humour through the study of the ambiguity, especially with respect to morphosyntactic and syntactic ambiguity. The results we have obtained show that it is possible to differentiate humorous from non humorous data through features like perplexity or sentence complexity.

We study the problem of automatically identifying humorous text from a new kind of text data, i.e., online reviews. We propose a generative language model, based on the theory of incongruity, to model humorous text, which allows us to leverage background text sources, such as Wikipedia entry descriptions, and enables construction of multiple features for identifying humorous reviews. Evaluation of these features using supervised learning for classifying reviews into humorous and non-humorous reviews shows that the features constructed based on the proposed generative model are much more effective than the major features proposed in the existing literature, allowing us to achieve almost 86% accuracy. These humorous review predictions can also supply good indicators for identifying helpful reviews.

We study the problem of automatically identifying humorous text from a new kind of text data, i.e., online reviews. We propose a generative language model, based on the theory of incongruity, to model humorous text, which allows us to leverage background text sources, such as Wikipedia entry descriptions, and enables construction of multiple features for identifying humorous reviews. Evaluation of these features using supervised learning for classifying reviews into humorous and non-humorous reviews shows that the features constructed based on the proposed generative model are much more effective than the major features proposed in the existing literature, allowing us to achieve almost 86% accuracy. These humorous review predictions can also supply good indicators for identifying helpful reviews.

This paper presents an artificial life environment based on Dynamic Fuzzy Cognitive Maps (DFCM) and inspired by Multi-Agent Systems, Machine Learning and concepts from classical FCM theory. The proposed architecture includes features such as a reinforcement learning algorithm to dynamically fine-tune the weights of the DFCM, a Finite States Machine, governing the behavior of the creatures by adding/removing concepts into the DFCM, and others. These features are used to add adaptability to the artificial creatures (agents) in a simulated hunter-prey environment with synthetic data. Some experiments carried out in a simulated virtual environment have showed promising results for further research in the subject of this study.

We propose a simple yet effective way to generate pun sentences that does not require any training on existing puns. Our approach is inspired by humor theories that ambiguity comes from the context rather than the pun word itself. Given a pair of definitions of a pun word, 1 our model first produces a list of related concepts through a reverse dictionary to identify unambiguous words to represent the pun and the alternative senses. We then utilize one-shot GPT3 to generate context words and then generate puns incorporating context words from both senses. Human evaluation shows that our method successfully generates puns 52% of the time, outperforming well crafted baselines and the state-of-the-art models by a large margin. * Equal contribution. † Work done when the author is interning at UCLA. 1 We focus on generating homographic puns where two or more meanings of a word form an intended humorous effect.

PoeTryMe is a poetry generation system that produces poems autonomously, from a set of initial parameters. After using a simplified version of this system, creative writers and other interested people identified some issues and expressed their wish to make changes in the resulting poems or to interact with the system and take part in the creative process. This paper illustrates some of the issues on generated poems and reports on a recent e↵ort towards providing alternative ways of using PoeTryMe and to meet the previous suggestions. Some functionalities were made available via a web API, which can now be exploited by other systems. Those include the generation of single lines, or the retrieval of related words, where additional constrains can be made on the number of syllables, sentiment or rhyme. On the top of this API, a co-creative interface has been developed. It enables users to start from scratch, from an existing poem, or to generate a new draft.

We introduce, release, and analyze a new dataset, called Humicroedit, for research in computational humor. Our publicly available data consists of regular English news headlines paired with versions of the same headlines that contain simple replacement edits designed to make them funny. We carefully curated crowdsourced editors to create funny headlines and judges to score a to a total of 15,095 edited headlines, with five judges per headline. The simple edits, usually just a single word replacement, mean we can apply straightforward analysis techniques to determine what makes our edited headlines humorous. We show how the data support classic theories of humor, such as incongruity, superiority, and setup/punchline. Finally, we develop baseline classifiers that can predict whether or not an edited headline is funny, which is a first step toward automatically generating humorous headlines as an approach to creating topical humor.

In this paper we introduce and discuss the apprentice framework, which we speculate can be used to plan and evaluate computational creativity projects. The framework defines a sequence of phases a system must follow in order to reach a level of creativity acceptable to a set of human judges. It also establishes four aspects of a creative piece susceptible of creative work. We mention some examples from different artistic disciplines. Our work focuses on establishing an environment as well as a team of people and machines to foster, study and monitor the emergence of creativity. On Human and Machine Creativity Assessing creativity in machines has become a prime issue in computational creativity after many systems have been built that exhibit a behavior that can intuitively be considered creative. The domains of such systems are so varied, and the versions of each one so many, that comparing them to one another or with different versions of themselves has become a hard task. Every sys...

Chalcone (1,3-diphenylprop-2-en-1-one) compounds are of natural or synthetic origins and possess a diversity in bioactivities. Recently, the inhibitory activities of heterocyclic chalcones against different cancer cell lines have raised much concern. The study aimed at synthesizing some heterocyclic chalcones and determining their in vitro cytotoxicity on rhabdomyosarcoma (RD) cell line. Heterocyclic chalcones in this study were developed on the basis of the idea that heteroaryl moieties either on ring A or ring B of chalcones might provide cytotoxicity on cancer cells. These compounds were prepared by Claisen-Schmidt condensation the in vitro cytotoxicity of the compounds on rhabdomyosarcoma (RD) cell line has been evaluated using the microculture tetrazolium (MTT) assay. A total of synthesized heterocyclic chalcones has been synthesized and their structures were elucidated by spectrometric methods. Bioassay results revealed that 5 out of 20 compounds showed activities against RD cells with IC 50 values less than 20μM. The compound 7 possessing two heterocyclic moieties (phenothiazine as A ring and thiophene as B ring) was considered as the most potential with IC 50 at 12.51 μM (compare with taxol having IC 50 at 10.88μM). The results demonstrate that heterocyclic chalcones are promising compounds for developing anticancer drugs.

In this paper we present a multi-modal framework for offline learning of generative models of object deformation under robotic pushing. The model is multi-modal in that it is based on integrating force and visual information. The framework consists of several sub-models that are independently calibrated from the same data. These component models can be sequenced to provide many-step prediction and classification. When presented with a test example-a robot finger pushing a deformable object made of an unidentified, but previously learned, material-the predictions of modules for different materials are compared so as to classify the unknown material. Our approach, which consists of offline learning and combination of multiple models, goes beyond previous techniques by enabling i) predictions over many steps, ii) learning of plastic and elastic deformation from real data, iii) prediction of forces experienced by the robot, iv) classification of materials from both force and visual data, v) prediction of object behaviour after contact by the robot terminates. While previous work on deformable object behaviour in robotics has offered one or two of these features none has offered a way to achieve them all, and none has offered classification from a generative model. We do so through separately learned models which can be combined in different ways for different purposes.

Robots are already present in people's lives as receptionists, caregivers and tutors. In human-robot interaction, social behavior is not only expected but often associated with users' confidence. Although several studies have been researching in this direction, the robot adaptation and the existing gap between the system and non-programming designers still need more effort to achieve success. In this paper, a cognitive architecture is proposed and implemented into a humanoid robot. The aim is to offer a framework programmable for controlling the robot's resources, approaching previous knowledge and new contents in educational interactive activities. Furthermore, the system adapts the robot's behavior according to objective measures of users attention and engagement during the activity. After the interactive sessions, these measures are provided in a graphical interface for students skills evaluation. Functions of visual classification, speech processing, autonomous web-search for new contents and attention detectors were tested and analyzed separately. This approach shows effectiveness in basic and medium condition levels from a set of sceneries for each module.

This study investigates the relationship between the phonemic content of texts in English and the emotional valence they inspire. The sublexical content is presented in terms of biphones composed by one vowel and one consonant. The statistical analysis of a vast corpus of emotionally evaluated sentences reveals a strong correlation between this sublexical presentation and the evaluations of valence provided by the readers. An initial test performed with other valence-rated prose texts makes believing that the feature observed within the corpus can be useful for the emotion classification of texts.

I investigate the intersection of the concepts ‘creativity’ and ‘computation’ in the context of improvised music. While these concepts are commonly thought of as opposites, I argue that they can be intimately interlinked when humans and computational systems contribute to improvised music performance. I take human creativity and computational creativity to be categorically different. However, computational creativity in improvised music may be grounded in a ‘knowing how’ to improvise computationally and may contribute to the distributed creativity of a human-machine performance system. The semantics of humans and computational systems are of different categories and their respective musical ‘purposefulness’ are also categorically different. However, these differences allow interaction; and when engaged in group improvisation both humans and computational systems can be engaged in contributing to a co-creative improvised music performance.