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Implementing feedback in creative systems : a workshop approach

Corneli, Joseph, Jordanous, Anna (2015) Implementing feedback in creative systems : a workshop approach. In: CEUR Workshop Proceedings. . CEUR Workshop Proceedings (KAR id:49540)

Abstract

One particular challenge in AI is the computational modelling and simulation of creativity. Feedback and learning from experience are key aspects of the creative process. Here we investigate how we could implement feedback in creative systems using a social model. From the field of creative writing we borrow the concept of a Writers Workshop as a model for learning through feedback. The Writers Workshop encourages examination, discussion and debates of a piece of creative work using a prescribed format of activities. We propose a computational model of the Writers Workshop as a roadmap for incorporation of feedback in artificial creativity systems. We argue that the Writers Workshop setting describes the anatomy of the creative process. We support our claim with a case study that describes how to implement the Writers Workshop model in a computational creativity system. We present this work using patterns other people can follow to implement similar designs in their own systems. We conclude by discussing the broader relevance of this model to other aspects of AI.

Item Type: Conference or workshop item (Paper)
Uncontrolled keywords: feedback, computational creativity, writers workshop
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76.E95 Expert Systems (Intelligent Knowledge Based Systems)
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76 Computer software > QA76.76.I59 Interactive media, hypermedia
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Anna Jordanous
Date Deposited: 15 Jul 2015 15:43 UTC
Last Modified: 05 Nov 2024 10:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/49540 (The current URI for this page, for reference purposes)

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