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arxiv: 2606.19136 · v1 · pith:ZEOZOGNKnew · submitted 2026-06-17 · 💻 cs.IT · math.IT

The Simplicity Paradox: Why Evolution Does Not Produce Universally Complex Agents

Pith reviewed 2026-06-26 19:22 UTC · model grok-4.3

classification 💻 cs.IT math.IT
keywords cognitive economybounded rationalityevolutionary selectionheterogeneous populationsdecision costssimplicityinformation processingdivision of labour
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The pith

Evolution favors populations with mostly simple agents and a few specialized complex decision-makers rather than universally complex ones.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper tackles the puzzle that information improves decisions yet humans and populations often avoid complexity and delegate judgment. It develops a theory of cognitive economy in which information has value but carries costs of acquisition, processing, and coordination. The key result is that in complex environments, selection can maintain heterogeneous populations: the majority uses low-cost heuristics while a minority or institutions specialize in information handling. This division reduces total decision costs while retaining most of the value created by knowledge, and the specialists can capture private gains that prevent a volunteer's dilemma. The framework unifies bounded rationality, rational inattention, hierarchy, markets, and cultural evolution by showing simplicity as an enabler of scalable organization rather than a defect.

Core claim

The central claim is that selection in complex environments can favor cognitive division of labour over uniform complexity. Societies composed of mostly simple agents plus a specialized decision-making centre dominate societies of uniformly complex agents when the costs saved by distributed simplicity exceed the utility lost through reduced autonomy and imperfect delegation. The specialised centre need not confront a volunteer's dilemma because its private payoff can exceed the payoff available under universal complexity via rents, status, control, or superior information.

What carries the argument

The cost-utility trade-off formalized by comparing uniform-complexity societies against heterogeneous societies that contain simple agents and one specialised decision-making centre.

If this is right

  • Heterogeneous populations can achieve lower total decision costs than uniform ones while preserving most knowledge value.
  • Bounded rationality and delegation become stable outcomes of selection rather than evolutionary failures.
  • Hierarchy and markets emerge as mechanisms that separate simple and complex roles.
  • Cultural evolution can sustain simplicity as a precondition for scalable social organization.
  • Specialized agents persist because their private gains do not require universal adoption of complexity.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same logic could be tested in artificial multi-agent systems where most agents use heuristics and a few handle planning.
  • It predicts that the share of specialists should rise with environmental complexity but remain a minority.
  • The model implies that attempts to force universal complexity, such as mandatory detailed education for all, may reduce overall welfare.

Load-bearing premise

The specialised decision-maker can obtain private payoffs higher than those available under universal complexity through rents, status, control or superior information.

What would settle it

Empirical observation that populations converge toward uniformly complex agents, without any persistent minority of specialists, as environmental complexity increases.

Figures

Figures reproduced from arXiv: 2606.19136 by Teddy Lazebnik.

Figure 1
Figure 1. Figure 1: Welfare comparison across environmental complexity. The figure compares uniformly simple, uniformly [PITH_FULL_IMAGE:figures/full_fig_p011_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Dominant social configuration in the (e, N) plane. Each point shows which configuration produces the highest total welfare [PITH_FULL_IMAGE:figures/full_fig_p012_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Decomposition of the welfare advantage of decision-compression over universal complexity. The dashed [PITH_FULL_IMAGE:figures/full_fig_p013_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Feasible transfer interval for decision-compression. The shaded region indicates values of [PITH_FULL_IMAGE:figures/full_fig_p014_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Role-choice payoffs as the number of decision-makers increases. The different line styles show the [PITH_FULL_IMAGE:figures/full_fig_p015_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Sensitivity of dominance regions to delegation-loss severity. Each panel shows the welfare-maximizing [PITH_FULL_IMAGE:figures/full_fig_p016_6.png] view at source ↗
read the original abstract

It has been well established that information improves decisions, pushing the population forward as more information becomes available. Nevertheless, a wide range of empirical evidence shows that humans avoid complexity, delegate judgement, and prefer simplified social worlds. This tension raises an evolutionary puzzle: if knowledge is economically valuable and therefore evolutionarily beneficial, why do populations not converge towards universally informed and complex agents? In this study, we propose a theory of cognitive economy in which information has positive utility but costly acquisition, processing, and coordination. In complex environments, selection can favour heterogeneous populations: most individuals use low-cost heuristics and simplified choice architectures, whereas a minority of agents or institutions specialize in information processing. This cognitive division of labour reduces decision costs while preserving much of the value created by knowledge. We formalize this trade-off by comparing societies of uniformly complex agents with societies containing simpler agents and a specialized decision-making centre. The latter can dominate when the costs saved by distributed simplicity exceed the utility lost through reduced individual autonomy and imperfect delegation. Crucially, the specialized decision-maker need not face a volunteer's dilemma, because its private payoff can exceed that available under universal complexity through rents, status, control or superior information. The framework links bounded rationality, rational inattention, hierarchy, markets, and cultural evolution, and suggests that simplicity is not a failure of adaptation but a precondition for scalable social organization.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

1 major / 0 minor

Summary. The manuscript proposes a theory of cognitive economy to explain why evolution does not produce universally complex agents despite information's value. It argues that selection in complex environments favors heterogeneous populations: most agents rely on low-cost heuristics and simplified architectures, while a minority or institutions specialize in information processing. This division of labor is formalized via a static comparison of uniformly complex societies against those with simpler agents plus a specialized decision-making center; the latter dominates when cost savings exceed lost utility from reduced autonomy and imperfect delegation. The specialist avoids the volunteer's dilemma because its private payoff can exceed universal-complexity payoffs via rents, status, control, or superior information. The framework connects bounded rationality, rational inattention, hierarchy, markets, and cultural evolution.

Significance. If the formal trade-off comparison can be shown to support evolutionary stability, the result would offer a coherent account of why simplicity persists and scales in social systems. It reframes observed human preferences for delegation and heuristics as adaptive rather than deficient, with potential to integrate disparate literatures on information costs and institutional design.

major comments (1)
  1. [Abstract] Abstract (formalization paragraph): the central claim that heterogeneous populations are evolutionarily favored rests on the assertion that 'the specialized decision-maker need not face a volunteer's dilemma, because its private payoff can exceed that available under universal complexity through rents, status, control or superior information.' This is stated without derivation from the described static society comparison of decision costs versus lost autonomy/utility. Without an explicit model of individual-level incentives, replicator dynamics, or a selection mechanism into the specialist role, the comparison alone does not establish that heterogeneity is stable or that any agent bears the specialization cost rather than free-riding.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for this precise observation on the scope of our formal argument. We address the comment below.

read point-by-point responses
  1. Referee: [Abstract] Abstract (formalization paragraph): the central claim that heterogeneous populations are evolutionarily favored rests on the assertion that 'the specialized decision-maker need not face a volunteer's dilemma, because its private payoff can exceed that available under universal complexity through rents, status, control or superior information.' This is stated without derivation from the described static society comparison of decision costs versus lost autonomy/utility. Without an explicit model of individual-level incentives, replicator dynamics, or a selection mechanism into the specialist role, the comparison alone does not establish that heterogeneity is stable or that any agent bears the specialization cost rather than free-riding.

    Authors: We agree that the manuscript's core formalization is a static welfare comparison between uniform-complexity and heterogeneous societies, and that this comparison alone does not derive individual incentives or demonstrate evolutionary stability via replicator dynamics. The statement on the specialist's private payoff is presented as a conceptual resolution to the volunteer's dilemma rather than a result formally extracted from the cost-utility equations. In revision we will (i) rephrase the abstract and introduction to state explicitly that the analysis identifies conditions under which heterogeneity yields lower aggregate decision costs for given utility loss, without claiming evolutionary stability, and (ii) add a limitations paragraph noting the absence of an explicit selection mechanism and identifying full dynamic modeling as future work. revision: yes

Circularity Check

0 steps flagged

No circularity; derivation remains self-contained without reduction to inputs.

full rationale

The provided abstract outlines a proposed theory comparing uniform-complexity societies to heterogeneous ones with a specialized center, asserting that private payoffs (rents, status, etc.) allow the specialist to avoid the volunteer's dilemma. No equations, formal derivations, or self-citations are quoted that would reduce any prediction or uniqueness claim to a fitted input or prior self-result by construction. The framework is presented as linking existing concepts (bounded rationality, hierarchy) via a static cost-utility trade-off, with no evidence of self-definitional loops or renamed empirical patterns. This meets the default expectation of no significant circularity.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract only; no explicit free parameters, axioms, or invented entities are stated. The cost of information processing and the private payoff advantage for specialists are invoked but not quantified or derived.

pith-pipeline@v0.9.1-grok · 5767 in / 940 out tokens · 23235 ms · 2026-06-26T19:22:27.339711+00:00 · methodology

discussion (0)

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