Open-Ended Evolution for Minecraft Building Generation
نویسندگان
چکیده
This paper proposes a procedural content generator which evolves Minecraft buildings according to an open-ended and intrinsic definition of novelty. To realize this goal we evaluate individuals' novelty in the latent space using 3D autoencoder, alternate between phases exploration transformation. During system multiple populations CPPNs through CPPN-NEAT constrained search (defined by current autoencoder). We apply set repair constraint functions ensure candidates adhere basic structural rules constraints during evolution. transformation, reshape boundaries identify new interesting areas solution retraining autoencoder with novel content. In study five different approaches for training transformation its impact on populations' quality diversity Our results show that can achieve better complexity compared static model, is further improved when larger datasets individuals diverse complexities.
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ژورنال
عنوان ژورنال: IEEE transactions on games
سال: 2022
ISSN: ['2475-1502', '2475-1510']
DOI: https://doi.org/10.1109/tg.2022.3189426