Is resource-rational analysis (Lieder & Griffiths) the tightest convergence point of Werbos's approximate dynamic programming and Anderson's rational analysis?

Direct-fetched and read the primary source: Lieder, F. & Griffiths, T. L. (2020), "Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources," Behavioral and Brain Sciences 43, e1 (target article + full open-peer-commentary + authors' response, 60 pages), via extract_pdf from https://cocosci.princeton.edu/papers/lieder_resource.pdf (TLS verified, no elevated-suspicion transport). This is the paper named in question-resource-rational-analysis-sharpest-werbos-anderson-bridge as the candidate tightest convergence point between Werbos's optimal-control/ADP lineage and Anderson's rational analysis. The full target-article bibliography and the full commentary/response bibliography (several hundred entries, alphabetized, read start to finish) were checked for "Werbos," "Bertsekas," "adaptive critic," "dynamic programming," and "Bellman."

Claim: Resource-rational analysis explicitly self-describes as a direct extension of Anderson's rational analysis

Lieder and Griffiths state their project in their own words: "Resource-rational analysis can be seen as an extension of rational-analysis from predicting behavior from the structure of the external environment to predicting cognitive mechanisms from internal cognitive resources and the external environment." The paper builds this out structurally — Anderson's rational analysis (Anderson 1990, The Adaptive Character of Thought) is given as a six-step method (Box 1: specify goals, model the environment, assume minimal computational limits, derive optimal behavior, test against data, iterate); resource-rational analysis is presented as a parallel five-step method (Box 2) that keeps Anderson's computational-level starting point but adds an explicit algorithm class, its resource costs, and a derivation of the algorithm that "optimally trades off resources and approximation accuracy." The paper frames this as "pushing the principles of rational analysis toward Marr's algorithmic level" — the same Marr computational/algorithmic distinction already in play in claim-rational-analysis-anderson-optimal-solution-marr-level. This is a technical-mechanism claim about the paper's own stated relationship to Anderson, sourced Tier 1 (primary text, direct quotation).

Claim: The AI-side lineage resource-rational analysis actually draws on is Horvitz and Russell's "bounded optimality," not Werbos's approximate dynamic programming

The paper's own account of where the "bounded" half of its synthesis comes from names a specific, different AI tradition: "AI researchers have already developed a theory of rationality that accounts for limited computational resources (Horvitz 1987; Horvitz et al. 1989; Horvitz 1990; Russell 1997; Russell & Subramanian 1995). Bounded optimality is a theory for designing optimal programs for agents with performance-limited hardware that must interact with their environments in real time." Lieder and Griffiths say they "apply the principle of bounded optimality to define a resource-rational mind" and describe their own paradigm as synthesizing and refining "these approaches" (Horvitz's and Russell's bounded optimality, plus Griffiths et al. 2015 and Lewis et al. 2014's cognitive-science uptake of it) — not approximate dynamic programming or the adaptive-critic architecture associated with Werbos. Searching the full target-article bibliography and the complete commentary/response bibliography (several hundred entries total, read end to end) turned up no citation to Werbos, Bertsekas, "adaptive critic," or "dynamic programming" anywhere in the paper. This is a technical-mechanism / historiographic claim about which AI tradition the paper cites as its formal antecedent; it rests on Tier 1 evidence (direct reading of the primary source's complete reference list), but it is a claim of absence — it shows Werbos is not part of this paper's stated lineage, not that no connection between ADP and resource-rationality could be drawn by later or adjacent work.

Claim: Resource-rational analysis formalizes the tradeoff as utility minus an explicit computational-cost term, not as a dynamic-programming recursion

The mechanism, stated in the paper's own equations: rational analysis defines optimal behavior as maximizing expected utility over outcomes (Equation 1, following von Neumann & Morgenstern 1944); resource-rational analysis instead defines the resource-rational heuristic as the one maximizing "the utility of the judgment, decision, or belief update" minus "the total opportunity cost of investing the cognitive resources... used or blocked by the heuristic... for the duration of its execution" (Equation 3, and its uncertainty-generalized form, Equation 4, which conditions on limited information i rather than the true environment E). The five-step method (Box 2) operationalizes this by positing a class of feasible algorithms and their costs, then deriving "the algorithm in this class that optimally trades off resources and approximation accuracy." This is the paper's own formal mechanism, quoted directly from the primary source — Tier 1.

Claim: Per this primary source, resource-rational analysis is a confirmed convergence with Anderson but not with Werbos — the hypothesis in the original question is not supported

Taken together, the three claims above answer the question this capture was commissioned to resolve. Resource-rational analysis is, on the paper's own explicit self-description, a real and tight convergence point — but only for one of the two lineages named in the question. It is directly, quotably, an extension of Anderson's rational analysis toward Marr's algorithmic level. But the "bounded optimization under real compute limits" half of the synthesis — the piece the open question hoped would connect to Werbos's approximate dynamic programming — is instead built on Horvitz and Russell's "bounded optimality" AI theory, a separate strand of 1980s–1990s AI research on resource-limited reasoning that is not part of the optimal-control / adaptive-critic / backpropagation-through-time lineage (claim-werbos-1968-cybernetica-earliest-germ, claim-werbos-backprop-from-freud-own-account) the question was asking about. Werbos's name, ADP, and the adaptive-critic architecture do not appear in the paper at all. So the specific hypothesis — that resource-rational analysis is where Werbos's ADP and Anderson's rational analysis meet — is not supported by the paper itself: one side of the proposed bridge holds (Anderson), the other side is a different bridge entirely (Horvitz/Russell bounded optimality). Whether some other, less direct connective tissue exists between Werbos's ADP and bounded optimality as AI traditions is not addressed by this source and is left as a further lead below.

Further leads

• Thomas Icard's "Resource Rationality: Toward a Theory of Cognitive Economy" (philpapers.org PDF) independently states the same Horvitz/Russell/bounded-optimality lineage for resource-rational analysis, corroborating claim 2 from a secondary angle — worth a direct read and Tier check (found via WebSearch, not yet fetched/verified as primary; [unverified-mechanism — needs primary read]).
• Whether Werbos's approximate dynamic programming / adaptive-critic tradition and Horvitz & Russell's bounded-optimality tradition ever cite or converge with each other (rather than each separately converging with cognitive science) is an open, better-scoped follow-up question — not addressed by any source checked in this capture.
• Anderson and Milson (1989), "Human memory: An adaptive perspective," is credited in the Lieder & Griffiths paper itself as arguably "the first application of the principle of bounded optimality in cognitive psychology" — a possible earlier convergence point worth checking against the same Werbos question, predating both Horvitz's and Lieder & Griffiths' explicit framings.
• The paper credits Griffiths, Lieder & Goodman (2015, "Rational Use of Cognitive Resources," Topics in Cognitive Science) and Lewis, Howes & Singh (2014, "Computational Rationality") as the immediate precursor papers that first fused bounded optimality with cognitive modeling, ahead of the 2020 BBS target article — earlier link in the same chain, not yet read directly.
• Several open-peer-commentary authors on the target article (e.g., Atmanspacher, Basieva, Busemeyer, Khrennikov — the quantum-probability commentary) propose alternative resource-rational axiomatizations; not explored here, tangential to the Werbos/Anderson question.

Entity candidates

• Falk Lieder — person — co-originator of resource-rational analysis; leads the Rationality Enhancement group at MPI Tübingen; recurring name if the vault builds out a resource-rationality cluster.
• Thomas L. Griffiths — person — co-originator of resource-rational analysis; Princeton; also behind Bayesian-cognition work already touching the vault via Oaksford & Chater adjacency.
• Eric Horvitz — person — originator (with Russell) of "bounded optimality," the actual AI-side antecedent of resource-rational analysis identified in this capture; currently uncovered in the vault.
• Stuart Russell — person — co-originator of "bounded optimality" (Russell & Subramanian 1995; Russell 1997); AI-safety-adjacent figure, currently uncovered in the vault.
• resource-rational analysis — concept — the paradigm itself; likely warrants its own concept note given how much it now connects (Anderson, Marr, bounded optimality, cognitive biases literature).
• bounded optimality — concept — Horvitz/Russell's AI theory of optimal programs for performance-limited hardware; distinct from and worth disambiguating against Werbos's approximate dynamic programming and against Simon's satisficing.