Posts Tagged ‘creativity’

Understanding the Creative Mind

Margaret Boden, a master at bring ideas from artificial intelligence and cognitive science to the masses, has done it again. In The Creative Mind: Myths and Mechanisms (published by Routledge, 2003), she has produced a well-written, well-argued review and synthesis of current computational theories relevant to creativity. This book seems appropriately pitched for students in survey courses and for the intelligent lay public. And if ever there were a topic suitable for bridging the gap between researchers adh the layperson, this is surely it: What is creativity, and how is it possible? Or, in computational terms (the terms that Boden argoes ought to be applied), what are the processes of creativity?

We believe that in order to analyze creative reasoning, one needs a theoretical framework in which to model thinking. To this end, we propose using a computational approach rooted in case-based reasoning. This paradigm is fundamentally concerned with memory issues, such as remindings from partial matches at varying levels of representation and the formation of analogical maps between seemingly disparate situations—exactly the kinds of phenomena that researchers up to, and including, Boden have highlighted as central to creativity.

Our research suggests that creativity is not a process in itself that can be turned on or off; rather, it arises from the confluence and complex interaction of inferences using multiple kinds of knowledge in the context of a task or problem and in the context of a specific situation. Much of what we think of as “creativity” arises from interesting strategic control of these inferences and their integration in the context of a task and situation.

These five aspects—inferences, knowledge, task, situation, and control—are not special or unique to creativity but are part of normal everyday thinking. They determine the thinkable, the thoughts the reasoner might normally have when addressing a problem or performing a task. In a specific individual, more creative thoughts will likely result when these pieces come together in a novel way to yield unexplored and unexpected paths that go “beyond the thinkable”.

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Understanding the Creative Mind

by Ashwin Ram, Linda Wills, Eric Domeshek, Nancy Nersessian, Janet Kolodner

Artificial Intelligence journal, 79(1):111-128, 1995
www.cc.gatech.edu/faculty/ashwin/papers/git-cc-94-13.pdf

Integrating Creativity and Reading: A Functional Approach

Reading has been studied for decades by a variety of cognitive disciplines, yet no theories exist which sufficiently describe and explain how people accomplish the complete task of reading real-world texts. In particular, a type of knowledge intensive reading known as creative reading has been largely ignored by the past research. We argue that creative reading is an aspect of practically all reading experiences; as a result, any theory which overlooks this will be insufficient.

We have built on results from psychology, artificial intelligence, and education in order to produce a functional theory of the complete reading process. The overall framework describes the set of tasks necessary for reading to be performed. Within this framework, we have developed a theory of creative reading. The theory is implemented in the ISAAC (Integrated Story Analysis And Creativity) system, a reading system which reads science fiction stories.

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Integrating Creativity and Reading: A Functional Approach

by Kenneth Moorman, Ashwin Ram

Sixteenth Annual Conference of the Cognitive Science Society (CogSci-94), Atlanta, GA, August 1994
www.cc.gatech.edu/faculty/ashwin/papers/er-94-10.pdf

A Model of Creative Understanding

Although creativity has largely been studied in problem solving contexts, creativity consists of both a generative component and a comprehension component. In particular, creativity is an essential part of reading and understanding of natural language stories. We have formalized the understanding process and have developed an algorithm capable of producing creative understanding behavior. We have also created a novel knowledge organization scheme to assist the process. Our model of creativity is implemented as a portion of the ISAAC (Integrated Story Analysis And Creativity) reading system, a system which models the creative reading of science fiction stories.

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A Model of Creative Understanding

by Kenneth Moorman, Ashwin Ram

Twelvth National Conference on Artificial Intelligence (AAAI-94), Seattle, WA, August 1994
www.cc.gatech.edu/faculty/ashwin/papers/er-94-04.pdf

Creative Conceptual Change

Creative conceptual change involves (a) the construction of new concepts and of coherent belief systems, or theories, relating these concepts, and (b) the modification and extrapolation of existing concepts and theories in novel situations. The first kind of process involves reformulating perceptual, sensorimotor, or other low-level information into higher-level abstractions. The second kind of process involves a temporary suspension of disbelieve and the extension or adaptation of existing concepts to create a conceptual model of a new situation which may be very different from previous real-world experience.

We discuss these and other types of conceptual change, and present computational models of constructive and extrapolative processes in creative conceptual change. The models have been implemented as computer programs in two very different “everyday” task domains: (a) SINS is an autonomous robotic navigation system that learns to navigate in an obstacle-ridden world by constructing sensorimotor concepts that represent navigational strategies, and (b) ISAAC is a natural language understanding system that reads short stories from the science fiction genre which requires a deep understanding of concepts that might be very different from the concepts that the system is familiar with.

Read the paper:

Creative Conceptual Change

by Ashwin Ram, Kenneth Moorman, Juan Carlos Santamaria

Invited talk at the 15th Annual Conference of the Cognitive Science Society, Boulder, CO, June 1993. Long version published as Technical Report GIT-CC-96/07, College of Computing, Georgia Institute of Technology, Atlanta, GA, 1996.
www.cc.gatech.edu/faculty/ashwin/papers/er-93-04.pdf