Abstract
The foundation of biological structures is self-replication. Neural networks are the prime structure used for the emergent construction of complex behavior in computers. We analyze how various network types lend themselves to self-replication. We argue that backpropagation is the natural way to navigate the space of network weights and show how it allows non-trivial self-replicators to arise naturally. We then extend the setting to construct an artificial chemistry environment of several neural networks.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Mathematik, Informatik und Statistik > Informatik |
Themengebiete: | 000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik |
Sprache: | Englisch |
Dokumenten ID: | 82284 |
Datum der Veröffentlichung auf Open Access LMU: | 15. Dez. 2021, 15:01 |
Letzte Änderungen: | 15. Dez. 2021, 15:01 |