Affiliations: [a] Alma Mater Studiorum Università di Bologna, Italy
| [b] University College London, United Kingdom, The Alan Turing Institute, United Kingdom, Alma Mater Studiorum Università di Bologna, Italy
Correspondence:
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Corresponding author: Giorgio Franceschelli, Alma Mater Studiorum Università di Bologna, Italy. E-mail: giorgio.franceschelli@unibo.it.
Abstract: Measuring machine creativity is one of the most fascinating challenges in Artificial Intelligence. This paper explores the possibility of using generative learning techniques for automatic assessment of creativity. The proposed solution does not involve human judgement, it is modular and of general applicability. We introduce a new measure, namely DeepCreativity, based on Margaret Boden’s definition of creativity as composed by value, novelty and surprise. We evaluate our methodology (and related measure) considering a case study, i.e., the generation of 19th century American poetry, showing its effectiveness and expressiveness.
Keywords: Computational creativity, deep learning, creativity measure, American
poetry
