A contributor produced by bounded development [ftip-00NA]

Specify a developmental process by an architecture, initial state, learning and action rules, an environment response law, and hard resource caps. The process generates an interaction history and a retained state \(Z\); from that state it induces a contributor \(v_Z\) of Definition [ftip-00MU]. States include learned parameters, habits, libraries and memories. Their existence must follow from the declared development, rather than from choosing an arbitrary helpful state after seeing the evaluation.

An initial library or teacher may already embody earlier learning. Treat that preparation as a disclosed inherited endowment, or include a bounded process producing it. The controlled comparison must not credit the current environment with structure already present before development begins.

Development may include other learners, teachers, language, tools and related tasks. Their response laws and relevant preparation are part of the specification. The source's developmental randomness, failed learning and failed contributions remain in the joint score distribution. An existence claim can supply one explicit developmental process with a proved quality guarantee. Selecting a lucky realized graduate is different: an affordable selection procedure must account for screening and failures, as in Definition [ftip-00MV].

A task-family parameter may be shared between development and fresh evaluation, allowing experience to be relevant. The development law and source-selection rule are fixed before final instance seeds are sampled. Conditional on the declared family parameter, those seeds are independent of development. The contributor receives neither the unrevealed instances nor their answers. Broadly useful structure acquired on earlier tasks is allowed; a secret determining the final answers is a different mechanism from the conceptual discovery sought here.

To isolate the environmental contribution, one controlled comparison starts copies with the same architecture, initial state, learning rules and development caps, then varies only their environmental access. This can establish an environmental effect for those processes. The lower-bound claim is stronger: it must still cover every closed campaign admitted by Definition [ftip-00MJ], rather than only the one control learner used in that comparison. Architecture, initial artifacts and permitted learning changes must remain explicit when moving from this control to a human–model study.