1. Gabor, T., Illium, S., Zorn, M., and Linnhoff-Popien, C. 2021. Goals for self-replicating neural networks. Artificial Life Conference Proceedings 33, MIT Press One Rogers Street, Cambridge, MA 02142-1209, USA journals-info …, 101.

Self-Replicator Analysis

This research delves into the innovative concept of self-replicating neural networks capable of performing secondary tasks alongside their primary replication function. By employing separate input/output vectors for dual-task training, the study demonstrates that additional tasks can complement and even stabilize self-replication. The dynamics within an artificial chemistry environment are explored, examining how varying action parameters affect the collective learning capability and how a specially developed ‘guiding particle’ can influence peers towards achieving goal-oriented behaviors, illustrating a method for steering network populations towards desired outcomes. [Gabor et al. 2021]