What the #®¥§≠$@ is Creativity?

Creativity is The Holy Grail of the Cognitive Sciences and it is very important for researchers in the Computer Sciences and AI fields. Although all attempts to explain and replicate intelligence have so far failed, the quest remains a key part of their research. This paper takes two innovative approaches. First, we see cognitive processes as involving rule-followingand as flexible, even chaotic, heuristics. This first concept uses a multi-heuristic concept without any complexes as mixed-cognition. Second, we propose abduction which, though seldom employed in this specific debate, is nonetheless a good way to explore creativity. Using both strategies, along with analysis of specific human creativity cases, we suggesta new cognitive paradigm that is both more realistic and truthful than hitherto. The idea is to offer a new way to achieve more powerful, complex artificial reasoning systems.

Annual plants in the floral design of the exhibition areas of the National Dendrological Park "Sofiyivka" of NAS of Ukraine

Aim. The National Dendrological Park "Sofiyivka" of the National Academy of Sciences of Ukraine is an example of the tandem of nature and human creativity, where a significant place in the formation of landscapes belongs to floral design. It is one of the most colorful architectural and artistic elements of landscaping. The aim is to describe and to define the main features of flower beds of the Dendrological Park “Sofiyivka”, and to describe the range of annual plants used in flower arrangements. Methods. The study was conducted in the dendrological park during 2019-2021. Examples of flower design have been described according to the classification of flower beds by V. V. Pushkar. Latin names of plant species were given according to “The Plant List, 2013”. Results. The analysis of flower design in the dendrological park “Sofiyivka” using annual plants was carried out. The features of flower beds are clarified by: shape and location, duration of their existence, flowering period, location of plants in the vertical plane and the type of plant combination. Conclusions. Five exhibition areas in “Sofiyivka” park have been defined. They are decorated with 12 flower compositions. This floral design belongs to the landscape and regular type of planning.

Comparison Of Achievement Sport Systems Between Indonesia And China

Sport as a model of human creativity is a form of physical activity that has very complex dimensions, which undergo a systematic process in the form of all activities or efforts that can encourage, arouse, develop and foster one's physical and spiritual potential. as individuals or members of society. in the form of games, competitions/contests, and intensive physical activities to obtain recreation, victory, and peak potential. Sport is currently a trend or lifestyle for some of the general public, even to the point of becoming a basic need in life. National development through the development of sports in Indonesia in this reform era has become a strategic vehicle, especially improving the quality of human resources, as well as the formation of the character and character of the nation, in this paper many factors play a role in success in the field of sports, one of which the author wants to examine the differences and similarities between the performance sports system that runs in Indonesia and China. This study aims to compare the development of achievement sports systems carried out in Indonesia and China in order to improve the quality and competence of sports. This study uses a qualitative descriptive method with data collection techniques through documentation studies. The results of this study conclude that the government's contribution is needed in preparing winning strategies, training facilities, increasing competition opportunities and increasing resources that can be assisted by a team of academics and researchers from universities to find new techniques in training to support the maximum use of sport science. Keywords: achievement sports system, Indonesia, China.

Extracting Creativity from Narratives using Distributional Semantic Modeling

Narrative text permeates our lives from job applications to journalistic stories to works of fiction. Developing automated metrics that capture creativity in narrative text has potentially far reaching implications. Human ratings of creativity in narrative text are labor-intensive, subjective, and difficult to replicate. Across 27 different story prompts and over 3,500 short stories, we used distributional semantic modeling to automate the assessment of creativity in narrative texts. We tested a new metric to capture one key component of creativity in writing – a writer’s ability to connect divergent ideas. We termed this metric, word-to-word semantic diversity (w2w SemDiv). We compared six models of w2w SemDiv that varied in their computational architecture. The best performing model employed Bidirectional Encoder Representations Transformer (BERT), which generates context-dependent numerical representations of words (i.e., embeddings). The BERT w2w SemDiv scores demonstrated impressive predictive power, explaining up to 72% of the variance in human creativity ratings, even exceeding human inter-rater reliability for some tasks. In addition, w2w SemDiv scores generalized across Ethnicity and English language proficiency, including individuals identifying as Hispanic and L2 English speakers. We provide a tutorial with R code (osf.io/ath2s) on how to compute w2w SemDiv. This code is incorporated into an online web app (semdis.wlu.psu.edu) where researchers and educators can upload a data file with stories and freely retrieve w2w SemDiv scores.

Evolution of the arts

This chapter examines both the biological and cultural evolution of the arts. Biological evolution of the arts deals with how humans evolved the species-specific capacities to create and appreciate artworks, while cultural evolution is about how artworks themselves, as cultural products, undergo changes in persistence over historical time and geographic location. The study of biological evolution includes both phylogenetic (or historical) and adaptationist (or Darwinian) approaches. The study of cultural evolution of the arts reveals the importance of a ‘creativity/aesthetics cycle’ in which the products of human creativity get appraised for their level of appeal by the aesthetic system, allowing them to either be transmitted to future generations or die out. This unification of creativity and aesthetics has far-reaching implications for both fields of study.

Composing and Improvising

Creativity is often associated with great composers or performers of the past who have been ascribed some kind of "creative mystique." In order to attain better explanatory power, the psychological perspective usually begins by defining musical creativity not by divine inspiration but rather as a generative process, that is, the act of generating new musical material or new renderings of pre-existing music. Musical generativity is best understood as a component of basic musicianship, rather than part of a specialized skill set. Despite creativity being of great interest to scholars for a very long time, only recently has scientific study of creativity borne some useful insights for musicians. This chapter shows how broader principles of human creativity, revealed by research across many domains, are also specifically applicable to music. It also explains the specific processes of composing and improvising music, showing that both require musicians to investment time and energy to build these creative skills to an expert level. Finally, this chapter encourages nurturing the naturally creative behaviors of childhood and facilitating in young musicians a exploratory mindset as a basic part of their musicianship.

Modeling and Learning Constraints for Creative Tool Use

Improvisation is a hallmark of human creativity and serves a functional purpose in completing everyday tasks with novel resources. This is particularly exhibited in tool-using tasks: When the expected tool for a task is unavailable, humans often are able to replace the expected tool with an atypical one. As robots become more commonplace in human society, we will also expect them to become more skilled at using tools in order to accommodate unexpected variations of tool-using tasks. In order for robots to creatively adapt their use of tools to task variations in a manner similar to humans, they must identify tools that fulfill a set of task constraints that are essential to completing the task successfully yet are initially unknown to the robot. In this paper, we present a high-level process for tool improvisation (tool identification, evaluation, and adaptation), highlight the importance of tooltips in considering tool-task pairings, and describe a method of learning by correction in which the robot learns the constraints from feedback from a human teacher. We demonstrate the efficacy of the learning by correction method for both within-task and across-task transfer on a physical robot.

Speeding up to keep up: exploring the use of AI in the research process

There is a long history of the science of intelligent machines and its potential to provide scientific insights have been debated since the dawn of AI. In particular, there is renewed interest in the role of AI in research and research policy as an enabler of new methods, processes, management and evaluation which is still relatively under-explored. This empirical paper explores interviews with leading scholars on the potential impact of AI on research practice and culture through deductive, thematic analysis to show the issues affecting academics and universities today. Our interviewees identify positive and negative consequences for research and researchers with respect to collective and individual use. AI is perceived as helpful with respect to information gathering and other narrow tasks, and in support of impact and interdisciplinarity. However, using AI as a way of ‘speeding up—to keep up’ with bureaucratic and metricised processes, may proliferate negative aspects of academic culture in that the expansion of AI in research should assist and not replace human creativity. Research into the future role of AI in the research process needs to go further to address these challenges, and ask fundamental questions about how AI might assist in providing new tools able to question the values and principles driving institutions and research processes. We argue that to do this an explicit movement of meta-research on the role of AI in research should consider the effects for research and researcher creativity. Anticipatory approaches and engagement of diverse and critical voices at policy level and across disciplines should also be considered.