Sheaf-Theoretic Transport and Obstruction for Detecting Scientific Theory Shift in AI Agents

ArXi:2605.14033v1 Announce Type: cross Scientific theory shift in AI agents requires than fitting equations to data. An artificial scientific agent must detect whether an existing representational framework remains transportable into a new regime, or whether its language has become locally-to-globally obstructed and must be extended. This paper develops a finite sheaf-theoretic framework for detecting theory-shift candidates through transport and obstruction.