emuloi

Emuloi is a term used to describe artificial or theoretical systems that are designed to emulate another system's behavior, structure, or processes. An emuloi seeks to reproduce both external performance and, where possible, the internal mechanisms that drive that performance, distinguishing it from simple simulation or replica.

Emuloi can be categorized as hard (physical replication) or soft (computational or abstract models). They can vary in fidelity: high-fidelity emuloi try to match internal states and decision rules; lower-fidelity ones approximate only outputs or surface behavior. Methods include state-space mapping, machine learning, rule-based replication, or hybrid approaches combining data-driven models with explicit theories.

The term has appeared in academic discussions and fiction since the early 21st century, without a single canonical definition, leading to diverse uses across AI research, neuroscience, robotics, and media studies. Emuloi are often proposed as tools for testing theories of learning, adaptation, and cognition, or as means to explore the consequences of duplicating another system's operation.

Within AI and robotics, emuloi can be used to study behavior transfer across domains, to reconstruct historical or biological systems for experimentation, or to create digital avatars that mimic a target agent. In neuroscience, neuroemuloi would model neural circuits to investigate function; in digital media, emuloi may animate characters by emulating real-world performers or organisms.

Discussion around emuloi includes questions of authenticity and rights, accountability for emulated agents, and potential harms from inaccurate representations or misuse of emulation technology.