Evolutionary computation for bottom-up hypothesis generation on emotion and communication
Through evolutionary computation, affective models may emerge autonomously in unanticipated ways. We explored whether core affect would be leveraged through communication with conspecifics (e.g. signalling danger or foraging opportunities). Genetic algorithms served to evolve recurrent neural networ...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-04-01
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| Series: | Connection Science |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/09540091.2020.1814203 |