E3 · cycle-001.e3-bra-greedy-marginal

Brazil, greedy, 20 years

100 simulations of 20 rounds from the 2026 position. Brazil decides by the greedy method; the shock and upside library, drawn at random each round.

Model 0.1.0 · graph 0.2.0 · parameters 0.1.0 · seeds 1–100 · elasticity sampled within each bracket

Every simulation · Compare with another experiment · More experiments like this

Not a forecast

Simulations of a structural model with seed parameter values, to compare methods and test the model. Other nations stay at their 2026 ratings throughout.

Outcome across simulations

The median at 2046, with the 10th to the 90th percentile of the 100 simulations under it.

Capability index: 13.62 (+1.93); From 11.69; 12.79 to 14.09
Rank by index: 21; From 30; 17 to 24
Domains at Tier 1: 1; From 0; 1 to 2
Tier rank: 13; From 33; 9 to 15

Capability index by round

Rank by index, by round

Every objective at the position and at the horizon
Objective	2026	10th percentile	Median	90th percentile	Better
Capability indexprimary	11.69	12.79	13.62	14.09	higher
Rank by index	30	17	21	24	lower
Tier rank	33	9	13	15	lower
Domains at Tier 1	0	1	1	2	higher
Score sum	843.9	923.8	983.3	1017.3	higher
Goal-weighted score	843.9	923.8	983.3	1017.3	higher
Resilient score	843.9	977.3 (mean score sum over the simulations)			higher

The capability index is the mean of the three dimensions, each the mean of its domains, each the mean of its groups. Tiers are Pareto layers within each domain; the tier rank orders nations by domains held at Tier 1, then Tier 2, and so on. The goal-weighted score is the score sum unless the experiment sets a goal. The primary objective is the one the experiment is judged on; every other objective is reported beside it.

Credits

What each round’s credits went on in the median simulation. Across all simulations, build took 23 per cent, buy took 44 per cent, partner took 33 per cent of the 2,068 credits a simulation spent on actions.

Report

Written from the simulation record by the loop's narrator. Every figure names the query it came from, in square brackets.

Batch cycle-001. Model 0.1.0, graph 0.2.0, parameters 0.1.0. 100 simulations, seeds 1 to 100; probes on 20. Every figure is a distribution over simulations of a structural model with seed parameter values; it shows what the model implies under these settings, not what will happen. Other nations are frozen at their 2026 ratings. No reconstructed historical data is used in this experiment.

Headline

Brazil played 20 rounds from 2026 under the greedy marginal method, with stochastic events, 100 times. Its capability index moved from 11.69 to a median of 13.62 (+1.93), with 90 per cent of simulations between 12.54 and 14.17 [experiment_objectives].

Starting position

In 2026 the nation ranks 30 on the index against the frozen field, holds 0 of nine domains at Tier 1 and has a tier rank of 33. Its base income is 386 credits a year, calibrated so that its 2026 position is affordable with headroom for investment.

What was decided

A simulation spent a median of 2,081 credits on moves. The five groups that took most were Fiscal Capacity & Public Finance (partner, 118 credits, 5.7 per cent); Research Talent & Knowledge Creation (buy, 110 credits, 5.3 per cent); Semiconductors & Advanced Computing (buy, 107 credits, 5.2 per cent); Foundational Education (build, 105 credits, 5.1 per cent); Digital & AI Competence (build, 96 credits, 4.6 per cent) [experiment_decisions_by_group]. By mode: buy 45 per cent, partner 32 per cent, build 23 per cent [experiment_decisions_by_group]. Concentration of spending (HHI) had a median of 0.038, and the most repeated action appeared in 30 per cent of rounds.

The leading domain by period: rounds 1 to 5, Human Capital; rounds 6 to 10, Trade & Investment; rounds 11 to 15, Trade & Investment; rounds 16 to 20, Critical Technology [experiment_spend_by_period].

The method's chosen action was within 5 per cent of its best alternative in 97 per cent of moves and ahead by more than 25 per cent in 0 per cent [experiment_decision_margins].

What the world did

A median simulation saw 2 shocks and 1 upside events. The most damaging per firing were S09 (9 firings in 9 simulations, −30.4 points each); S10 (3 firings in 3 simulations, −30.3 points each); S05 (8 firings in 8 simulations, −28.7 points each) [experiment_shocks]. Upside events fired 96 times across all simulations [experiment_shocks].

The groups that lost most to shocks, per simulation: Fiscal Capacity & Public Finance −1.06; Information Environment & Strategic Communication −0.91; Digital & Services Trade −0.87; Trade Facilitation & Logistics −0.87 [experiment_shock_damage_by_group].

The edges that carried most change through the graph, per simulation: Semiconductors & Advanced Computing to Artificial Intelligence (+1.11 points); Economic Output & Productivity to Fiscal Capacity & Public Finance (+0.56 points); Research Talent & Knowledge Creation to Biotechnology & Health Technologies (+0.63 points) [experiment_propagation_by_edge].

Where it ended

At 2046 the median rank is 21 (5th to 95th percentile 17 to 25), the median count of Tier 1 domains 1 (1 to 2) and the median tier rank 13; the resilient score, the mean score sum over simulations, is 977 [experiment_objectives].

Tier 1 probability changed most in: human capital (0 to 99 per cent of simulations); trade and investment (0 to 22 per cent of simulations) [experiment_tiers_by_round].

Why

Without shocks the index ends +0.758 higher on average, so the shocks cost about 0.758 index points [experiment_probe_attribution].

Holding instead of following this method changes the index by −2.403: that is the method's worth against doing nothing [experiment_probe_attribution].

Removing any single one of the five largest actions changes the index by between −0.022 and −0.018, for example 2046 buy Semiconductors & Advanced Computing (24 credits) [experiment_probe_attribution]. The largest actions by credits come late, when income is highest, and are rarely the most valuable.

Removing the largest shock of a simulation raises the index by +0.394 on average [experiment_probe_attribution].

The replay probe reproduces the simulations exactly (index change 0.000000), so the attributions are clean [experiment_probe_attribution].

Surprises

tier_jump (warn): largest gain in one domain within five years: 6 tiers (100 simulations above 2).

saturation_high (warn): 64% of simulations end with a group at 20 that did not start there (median 1 groups).

retired_words (warn): e3-bra-greedy-marginal/report.md: 'simulations' 2 time(s), first near line 40; use 'simulations'.

The simulation furthest from the median (seed 33) ends −1.69 from it, with 7 shocks and 0 upside events [experiment_outlier_simulations].

Comparison

Against the hold experiment for the same nation (e3-bra-hold), the median index is +2.38 points apart, the median rank 21 against 34, and Tier 1 domains 1 against 0 [experiment_against_hold].

No backcast comparison: this experiment does not start from a historical position [experiment_against_history].

What each decision and shock was worth

Counterfactual probes on the first 20 seeds: the same simulations with one thing changed, paired seed by seed. A removed decision or shock is taken out and the other decisions replayed unchanged, so the difference is that item's worth.

Probe	Index	Score sum	Tier 1	For example
Hold instead of the method	−2.403	−172.3	−1.25
No shocks	+0.758	+54.2	−0.20
Replay of the recorded actions (must change nothing)	0.000	0.0	0.00
Without the 1st largest decision	−0.019	−1.4	0.00	2046 buy Semiconductors & Advanced Computing (24 credits)
Without the 2nd largest decision	−0.019	−1.4	0.00	2046 buy Energy Technologies (24 credits)
Without the 3rd largest decision	−0.022	−1.5	0.00	2046 buy Development Cooperation & Global Assistance (24 credits)
Without the 4th largest decision	−0.018	−1.4	0.00	2046 buy Research Talent & Knowledge Creation (24 credits)
Without the 5th largest decision	−0.020	−1.4	0.00	2046 buy Robotics & Autonomous Systems (24 credits)
Without the 1st largest shock	+0.394	+27.6	+0.58	2039 S03 (-12.0 points)
Without the 2nd largest shock	+0.288	+20.3	+0.29	2033 S04 (-12.0 points)
Without the 3rd largest shock	+0.238	+16.8	+0.10	2038 S03 (-8.3 points)

Simulations

Three simulations told round by round, each on its own page: the one nearest the median index at the horizon, and those nearest the 10th and the 90th percentile. Every one of the 100 is listed with its outcome on the simulations page.

All 100 simulations

Events

How often each shock and upside event began across the simulations. Shocks come from the ten downside scenarios and upside events from the ten upside ones, at their yearly likelihood.

Event	Kind	Simulations	Mean round	Points
Regional war spillover S03	Shock	31 per cent	10.6	−9.6
Hybrid coercion S04	Shock	29 per cent	8.9	−16.6
AI labour shock S08	Shock	29 per cent	10.3	−24.9
Breadbasket failure S06	Shock	28 per cent	9.8	−9.8
Global funding seizure S02	Shock	26 per cent	10.3	−19.0
Trade bloc rupture S01	Shock	22 per cent	8.7	−18.9
Market access opening S12	Upside	19 per cent	9.1	+10.3
Water-efficient food leap S16	Upside	19 per cent	10.5	+8.1
Chronic disease advance S19	Upside	16 per cent	10.8	+16.3
Clean power threshold S15	Upside	14 per cent	12.3	+6.2
Automated discovery step S17	Upside	13 per cent	14.7	+15.6
Core disaster S07	Shock	10 per cent	7.1	−26.6
Cryptographic trust break S09	Shock	9 per cent	10.3	−30.4
Legitimacy rupture S05	Shock	8 per cent	9.5	−28.7
Outbreak defence succeeds S20	Upside	3 per cent	4.3	+17.7
Middle East settlement S14	Upside	3 per cent	5.0	+4.2
Severe pandemic S10	Shock	3 per cent	10.0	−30.3
Public service leap S18	Upside	2 per cent	11.5	+13.1
Debt service reset S11	Upside	2 per cent	8.5	+5.5
Great-power détente S13	Upside	1 per cent	8.0	+6.1

Groups across simulations

Every capability group: its position, and its median and spread at the horizon across the simulations, with what the method spent on it.

Find a group

Domain

73 of 73 groups

Capability group	Domain	2026	2046	Change	Levels invested	Credits
Digital & AI Competence	Human Capital	10.50	19.19 18.48 to 19.64	+8.69	8.32	96
Artificial Intelligence	Critical Technology	9.33	17.42 16.79 to 18.00	+8.09	7.17	91
Lifelong Learning & Reskilling	Human Capital	10.67	18.17 17.57 to 18.54	+7.50	7.48	77
Technical & Vocational Skills	Human Capital	12.50	20.00 19.69 to 20.00	+7.50	8.30	94
Semiconductors & Advanced Computing	Critical Technology	5.33	12.39 11.60 to 13.03	+7.06	7.39	107
Connectivity, Cyber & Trust Technologies	Critical Technology	9.40	16.27 15.60 to 17.02	+6.87	7.22	89
Technology Adoption & Diffusion	Production & Innovation	11.50	18.19 17.46 to 18.70	+6.69	6.26	80
Alliances & Security Cooperation	Information & Influence	12.00	18.63 17.85 to 19.25	+6.63	7.20	81
Development Cooperation & Global Assistance	Information & Influence	10.00	16.38 15.20 to 16.99	+6.38	6.30	82
Research Talent & Knowledge Creation	Human Capital	11.67	17.60 16.95 to 18.13	+5.93	5.39	111
Foundational Education	Human Capital	11.25	17.15 15.39 to 18.59	+5.90	5.98	105
Advanced Education	Human Capital	13.00	18.09 16.55 to 18.86	+5.09	4.36	77
Robotics & Autonomous Systems	Critical Technology	8.25	13.16 11.77 to 13.75	+4.91	4.46	61
Economic Output & Productivity	Production & Innovation	12.00	16.56 15.52 to 17.10	+4.56	4.57	92
Investment Attraction & Projection	Trade & Investment	12.33	16.85 16.10 to 17.69	+4.52	5.11	74
Global Value Chain Position	Trade & Investment	11.67	16.09 15.07 to 16.78	+4.42	4.69	64
Export Capability & Sophistication	Trade & Investment	11.67	15.88 14.84 to 16.67	+4.21	4.72	64
Trade Facilitation & Logistics	Trade & Investment	12.00	16.09 15.02 to 16.92	+4.09	4.72	65
Trade Policy & Market Access	Trade & Investment	14.25	18.33 17.77 to 18.92	+4.08	4.61	55
Fiscal Capacity & Public Finance	Financial Strength	12.50	16.51 15.72 to 17.14	+4.01	4.34	118
Economic Leverage & Dependence	Trade & Investment	11.33	14.94 13.98 to 15.57	+3.61	3.57	46
Sensing, Timing & Navigation	Critical Technology	8.80	12.06 11.20 to 12.57	+3.26	3.44	46
Energy Technologies	Critical Technology	9.80	13.00 12.26 to 13.49	+3.20	3.15	46
Digital & Services Trade	Trade & Investment	12.00	15.16 13.80 to 15.72	+3.16	3.36	44
Advanced Materials & Manufacturing	Critical Technology	10.43	12.34 11.42 to 13.46	+1.91	2.01	29
Information Environment & Strategic Communication	Information & Influence	11.33	13.13 11.97 to 14.14	+1.80	2.43	33
Sovereign Capital & External Financial Power	Financial Strength	10.80	12.28 11.34 to 12.81	+1.48	1.61	23
Communications & Digital Infrastructure	Strategic Infrastructure	13.43	14.74 13.88 to 15.38	+1.31	1.44	26
Strategic Strike & Missile Defence	National Security	6.33	7.61 6.01 to 8.06	+1.28	1.35	19
Space Technologies	Critical Technology	9.33	10.50 9.63 to 10.96	+1.17	1.28	23
Regulatory Governance & Strategic Controls	Governance & Integrity	10.67	11.70 9.99 to 13.33	+1.03	1.30	26
Diplomatic Statecraft & Global Networks	Information & Influence	14.25	15.24 14.02 to 16.01	+0.99	1.09	18
Innovation & Commercialisation	Production & Innovation	11.00	11.67 10.66 to 12.28	+0.67	0.00	0
Cyber & Electromagnetic Operations	National Security	9.33	9.97 9.36 to 11.10	+0.64	0.55	8
Advanced Manufacturing	Strategic Infrastructure	13.80	14.34 13.58 to 14.87	+0.54	0.00	0
Biotechnology & Health Technologies	Critical Technology	12.60	12.97 12.15 to 13.70	+0.37	0.00	0
Social Infrastructure	Strategic Infrastructure	12.73	12.98 12.20 to 13.65	+0.25	0.00	0
Quantum Technologies	Critical Technology	6.25	6.42 5.61 to 6.95	+0.17	0.00	0
Force Generation & Mobilisation	National Security	12.67	12.84 12.16 to 13.16	+0.17	0.00	0
Intelligence & Assessment	National Security	11.00	11.16 10.21 to 11.61	+0.16	0.00	0
Resource Infrastructure	Strategic Infrastructure	16.00	16.14 15.52 to 16.72	+0.14	0.00	0
Health System Capability	Human Capital	13.00	13.14 12.62 to 13.67	+0.14	0.00	0
Transport Infrastructure	Strategic Infrastructure	13.38	13.48 12.81 to 14.07	+0.10	0.00	0
Space, Aerospace & Defence Infrastructure	Strategic Infrastructure	12.50	12.56 11.99 to 13.03	+0.06	0.00	0
Culture, Language & Education Diplomacy	Information & Influence	13.60	13.63 12.70 to 14.16	+0.03	0.00	0
Nuclear Deterrence	National Security	0.00	0.00 0.00 to 0.13	0.00	0.00	0
Water, Sanitation & Waste Infrastructure	Strategic Infrastructure	12.20	12.18 11.35 to 12.75	−0.02	0.00	0
Labour & Employment	Production & Innovation	11.00	10.96 9.54 to 11.58	−0.04	0.00	0
Political Institutions & Civic Participation	Governance & Integrity	14.00	13.95 13.22 to 14.38	−0.05	0.00	0
Air Power	National Security	12.00	11.92 11.39 to 12.23	−0.08	0.00	0
Population Health	Human Capital	11.33	11.24 10.67 to 11.68	−0.09	0.00	0
Land Power	National Security	12.00	11.86 11.24 to 12.18	−0.14	0.00	0
Early Childhood Development	Human Capital	13.00	12.86 12.31 to 13.30	−0.14	0.00	0
Government Effectiveness & Public Administration	Governance & Integrity	13.20	13.05 12.07 to 13.76	−0.15	0.00	0
Transparency, Oversight & Accountability	Governance & Integrity	12.67	12.51 11.92 to 12.87	−0.16	0.00	0
National Resilience & Crisis Management	Governance & Integrity	12.20	12.04 11.34 to 12.52	−0.16	0.00	0
Structural Transformation & Complexity	Production & Innovation	11.67	11.51 10.66 to 12.05	−0.16	0.00	0
Justice System & Fundamental Rights	Governance & Integrity	11.50	11.31 10.70 to 11.70	−0.19	0.00	0
Public Integrity & Anti-Corruption	Governance & Integrity	12.00	11.81 11.22 to 12.22	−0.19	0.00	0
Space Operations	National Security	7.33	7.14 6.57 to 7.71	−0.19	0.18	3
Energy Infrastructure	Strategic Infrastructure	14.00	13.80 12.88 to 14.51	−0.20	0.00	0
Joint Command, Projection & Sustainment	National Security	11.50	11.30 10.68 to 11.64	−0.20	0.00	0
Agriculture & Food Infrastructure	Strategic Infrastructure	14.25	13.98 13.26 to 14.50	−0.27	0.00	0
Internal Security & Order	Governance & Integrity	10.67	10.39 9.68 to 10.87	−0.28	0.00	0
Diaspora & Global Communities	Information & Influence	10.00	9.70 8.84 to 10.09	−0.30	0.00	0
Monetary & Currency Capability	Financial Strength	14.33	14.03 12.39 to 14.68	−0.30	0.00	0
Financial Infrastructure	Strategic Infrastructure	15.75	15.43 14.55 to 15.91	−0.32	0.00	0
Maritime Power	National Security	12.00	11.66 10.87 to 12.04	−0.34	0.00	0
Business Dynamism & Entrepreneurship	Production & Innovation	11.50	11.14 10.23 to 11.69	−0.36	0.00	0
Industrial & Sectoral Base	Production & Innovation	14.50	14.08 13.14 to 14.76	−0.42	0.00	0
Financial System Depth & Access	Financial Strength	14.20	13.74 12.47 to 14.32	−0.46	0.00	0
Financial Regulation & Integrity	Financial Strength	13.25	12.78 11.50 to 13.39	−0.47	0.00	0
Financial Stability & Crisis Management	Financial Strength	13.67	13.19 11.89 to 13.78	−0.48	0.00	0

Checks

The automated checks run on this experiment before anything was written about it. A warning is a candidate finding for the improvement loop.

passcredits_conservedlargest gap between credits in and credits accounted for: 1.1e-13
passscores_in_boundsscores range 0.000 to 20.000
passno_nans0 missing values in the trajectory and objectives
passprobe_replay_reproducesthe recorded moves played back reproduce the simulation to within 0.0e+00 points (20 simulations)
passledger_balancesthe edge ledger sums to the propagated change to within 9.7e-07 points
passmove_without_shocklargest one-year move in a group with no shock landing: 2.15 points; 0% of simulations have one above 3
warntier_jumplargest gain in one domain within five years: 6 tiers (100 simulations above 2)
passall_tier1_from_outside_top10starting rank 30; 0 simulations reach Tier 1 in all nine domains
warnsaturation_high64% of simulations end with a group at 20 that did not start there (median 1 groups)
passsaturation_low0% of simulations end with a group at 0 that did not start there (median 0 groups)
passspend_concentrationmedian concentration of spending across groups (HHI) 0.038; most funded group economic.financial_strength.fiscal_capacity_and_public_finance
passsame_actionthe most repeated move (group and mode) appears in a median 30% of rounds

Settings and versions

Experiment cycle-001.e3-bra-greedy-marginal. Every simulation records the model, graph and parameter versions, the scenario, the method and its seed, so it can be reproduced exactly.

Nation: Brazil (BRA)
Position: The 2026 ratings of the National Capability Index
Method: Greedy. Each round, the actions with the most value per credit: a level's own worth plus its long-run effect downstream through the graph, less the maintenance it will need, counting only what arrives before the horizon.
Scenario: The shock and upside library, drawn at random each round
Objective: Capability index, the primary objective the experiment is judged on; every other objective is reported beside it
Horizon: 20 rounds, 2026 to 2046
Simulations: 100 seeds, 1 to 100. Every method in the batch faces the same draws for the same seed.
Graph elasticities: Drawn for each simulation, uniformly within each edge’s bracket
Income: Base credits 386.4 a round, moving with the economic groups
Versions: Model 0.1.0, Capability Dependency Graph 0.2.0, parameters 0.1.0
Batch: Improvement cycle (cycle-001), cycle 1 of the improvement loop
Runtime: 7.1 seconds in all; 1083 microseconds a round

Not a forecast: Every figure is a distribution over the simulations of a structural model, reported to compare methods and test the model. None is a prediction of what a nation will do or become.
Structural parameters: Costs, decay, vulnerability and credits are structural seed values with low or medium confidence, set by domain with single-group exceptions. Five groups have no defensible value in a single-nation model and are flagged in the parameter tables.
Other nations are frozen: One nation is simulated at a time. Every other nation stays at its 2026 rating, so rank and tiers are measured against a still field; where the simulated nation rises past others their own tiers are not re-sorted.
Starting depth and mode are defaults: The position is the National Capability Index ratings. How institutionalised each capability is, and how much was built, bought or partnered, have no data behind them yet and start from structural defaults.
Credits are calibrated, not measured: Each nation’s income is set so that its position is affordable with headroom that rises with its fiscal capacity. It is not yet fiscal capacity as a share of GDP.