Creativity and Machine Learning: A Survey
Fuente:
arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2021
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| Subjects: | |
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| _version_ | 1866916610686582784 |
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| author | Franceschelli, Giorgio Musolesi, Mirco |
| author_facet | Franceschelli, Giorgio Musolesi, Mirco |
| contents | There is a growing interest in the area of machine learning and creativity. This survey presents an overview of the history and the state of the art of computational creativity theories, key machine learning techniques (including generative deep learning), and corresponding automatic evaluation methods. After presenting a critical discussion of the key contributions in this area, we outline the current research challenges and emerging opportunities in this field. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2104_02726 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Creativity and Machine Learning: A Survey Franceschelli, Giorgio Musolesi, Mirco Machine Learning Artificial Intelligence Computers and Society There is a growing interest in the area of machine learning and creativity. This survey presents an overview of the history and the state of the art of computational creativity theories, key machine learning techniques (including generative deep learning), and corresponding automatic evaluation methods. After presenting a critical discussion of the key contributions in this area, we outline the current research challenges and emerging opportunities in this field. |
| title | Creativity and Machine Learning: A Survey |
| topic | Machine Learning Artificial Intelligence Computers and Society |
| url | https://arxiv.org/abs/2104.02726 |