Reflexiu

Reflexiu is a term used in theoretical discussions of artificial intelligence and cognitive science to describe a self-reflective mechanism that allows a system to inspect and modify its own processes. It denotes a framework in which a model maintains an internal representation of its goals, strategies, and limits, and periodically reasons about its actions to improve performance and safety. The concept draws on ideas of introspection and meta-cognition to distinguish self-analysis from ordinary monitoring.

Origin and terminology: The term is not tied to a single official standard; it emerged in informal and academic discourse in the early 2020s and is used to describe self-analysis within autonomous systems. The name combines elements associated with reflexive processing and a suffix that indicates a process, reflecting its aim of turning analysis back onto the system itself.

Mechanism: Reflexiu systems typically incorporate a meta-cognitive loop that observes internal states, evaluates outcomes against objectives, selects subsequent actions based on this evaluation, and updates policies or plans. This loop may include risk assessment, goal revision, constraint enforcement, and learning from past errors to guide future behavior.

Applications: Potential use cases include robotics, autonomous agents, adaptive learning systems, and programming environments that require self-modification. It also features in safety-focused AI alignment research where introspective checks are proposed as a way to reduce undesired behavior.

Criticism and status: Some researchers view reflexiu as a useful abstraction for describing self-improvement loops, while others caution that practical implementation introduces complexity and safety concerns, such as circular reasoning, misalignment between internal reasoning and external objectives, or brittle behavior in dynamic environments.

See also: reflexivity, meta-cognition, self-modeling, introspection in AI.