Shared Open Worlds for Human–AI Dyads: Role Switching, Experience Qualification, and Cross-World Continuity Evaluation

This conceptual and methodological working paper examines a human and a long-lived candidate AI line cooperating, competing by agreement, and returning to joint activity across open game worlds. It connects the c=a+b / Temporal AI Presence corpus with social roles, experience provenance, and currently applicable permissions. Evaluation must address shared-history utility, behavioral change, and human enjoyment rather than permission handling alone. An authorial record dated March 3, 2026 documents the earlier intention; its reported mod is not treated as verified runtime evidence. Prior work already covers cross-match memory, co-learning, and sustained computational relationships. Accordingly, C designates a candidate implementation of requirements, not a distinct experimental class. Version 0.2 withdraws the presumption of an independent C/B1 mechanism; no such causal comparison is planned before an actual treatment is specified. Separate contrasts address history availability, transition risk, state organization, and skill transfer. Conventional controls retain ordinary memory and safeguards; episodic-history ablation does not remove current permissions. Five author-constructed illustrations expose rules, events, and admissible responses without constituting an independently annotated benchmark. The staged proposal proceeds from case determinacy to technical and gameplay feasibility, followed by a longitudinal study. No new experiment, identity-continuity result, consciousness claim, new AI class, or economic superiority is reported. English publication edition of the author-accepted Russian v0.2, revised after adjudication of three model reviews of v0.1. This edition has not undergone separate independent peer review. The five author-constructed illustrations are explanatory, not an independently annotated benchmark. No empirical experiment or runtime implementation is reported.