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Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials

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Published on: November 15, 2014

Computational Social Creativity.

Rob Saunders, Oliver Bown¹

¹University of Sydney.

Artificial Life

|August 18, 2015

Summary

This review explores computational social creativity, modeling how social interactions foster creative development. Computational models offer unique insights into creativity as a social phenomenon, advancing the field through established methodologies.

Area of Science:

Computational Social Science
Artificial Intelligence
Cognitive Science

Background:

Creativity is increasingly studied as a social phenomenon.
Computational models of individual creativity exist.
Computational modeling is applied to social phenomena.

Purpose of the Study:

To review the development of computational models of creativity with central social interactions.
To define and contextualize computational social creativity.
To identify key themes and opportunities in this research area.

Main Methods:

Literature review of computational models of social creativity.
Analysis of common requirements from artificial life and computational social science simulations.

Keywords:

Social creativity computational creativity computational social science multi-agent modeling

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Identification of key themes in computational social creativity research.

Main Results:

Computational social creativity is a critical area for understanding creativity socially.
Methodologies from artificial life and computational social science are applicable.
Integrating social and individual creativity models presents opportunities and challenges.

Conclusions:

Computational social creativity offers unique epistemological contributions to understanding creativity.
Existing simulation methodologies can be directly applied.
Future work should focus on integrated models combining social and individual creativity.