eignaleika

Eignaleika is a fictional concept used in speculative discussions of autonomous systems and narrative world-building. It denotes a self-referential modeling process that helps an agent maintain a coherent identity across changing inputs by generating and updating an internal self-representation.

Etymology and origin: The term is credited to a fictional author-scientist, L. M. Harrow, in a late-21st-century setting, with roots intended to evoke “own likeness.” It is constructed for the sake of discussion and does not correspond to an established scientific term.

Concept and mechanisms: Eignaleika draws on ideas from self-model theory and predictive processing. An agent maintains a hierarchical internal model that is tagged with self-signals, enabling the system to distinguish actions and observations that pertain to its own state from external data. By comparing predicted consequences with actual outcomes, the system adjusts both its decision policy and its memory updates to minimize identity drift, while still allowing adaptive change when warranted.

Applications and context: In AI theory and science-fiction scholarship, eignaleika is used as a lens to explore how agents can remain identifiable over long periods and through environmental shifts. It provides a framework for discussing memory coherence, long-term autonomy, and the balance between stability of self and flexibility of behavior. As a narrative device, it helps depict characters or machines that resist abrupt or ungrounded transformations.

Critique and status: Within fictional contexts, proponents highlight the value of a self-consistent internal model. Critics argue that, without empirical grounding, the concept remains abstract and risks overlapping with existing self-model or meta-representation frameworks.

See also: self-model, predictive processing, autopoiesis, identity persistence.