Continuity Computing: A Framework for Cross-Embodiment Cognitive State Transfer and Persistent AI Identity

Continuity Computing is a systems architecture for achieving seamless
continuity of cognitive, identity, embodiment, and task state across
heterogeneous computational environments. It defines a unified framework for
extracting, serializing, transferring, and reconstructing AI cognitive state,
allowing agents and AI systems to move fluidly between devices, robots,
XR environments, multi-agent ecosystems, and physical or virtual contexts.

The Continuity Computing architecture introduces the Embodiment Interface Layer
(EIL), Informational State Engine (ISE), Environment Graph Engine (EGE), and
Continuity Runtime (CRT/CIE). These components produce a Transfer State Packet
(TSP) which is a portable, container-agnostic representation of physical state,
informational state, reasoning context, persona modulation, affective state,
and environmental bindings. The Reconstruction Runtime (RRT) decodes and
reconstitutes state in a target embodiment or environment.

This technical report describes the theoretical foundations, systems design,
continuity semantics, identity-state modeling, safety constraints, failure
modes, reconstruction logic, and end-to-end data flow of Continuity Computing.
It provides a foundation for next-generation AI systems capable of maintaining
persistent cognitive continuity across space, time, devices, and embodiments.