Round 1 · simulation 27 · mcts-m2.m2-gbr-mcts-tier-rank

Round 2027

Round 1 of 20 in simulation 27 of United Kingdom, tree search, 20 years: 5 actions, and the index +0.038 to 16.49.

Model 0.1.0 · graph 0.2.0 · parameters 0.1.0

State in and state out

The simulation as it came into 2027 (the end of 2026) and as it left it.

Capability index
16.49 (+0.038)
In: 16.45
Rank by index
3
In: 3
Domains at Tier 1
3
In: 2
Credits carried
103
In: 0
Each domain's mean score and tier coming in and going out
DomainInOutChangeTier
Critical Technology16.1616.160.0003
Strategic Infrastructure16.0316.030.0002
National Security16.2816.280.0002
Human Capital16.1816.52+0.3392 → 1
Information & Influence17.1517.150.0002
Governance & Integrity16.4816.480.0001
Financial Strength17.3617.360.0002
Production & Innovation15.9215.920.0001
Trade & Investment16.5416.540.0003

Decision, shocks and propagation

What happened in 2027: the credits, the tree search (mcts) method's decision and its actions, any shocks and upside events, the tier changes, and the groups that moved most, split into what was invested, lost to decay, struck by events and carried through the dependency graph.

Credits. Income 951. Maintenance 610. Spent 238 on actions (build 238). 103 carried over.

  • BuildTechnical & Vocational Skills48 credits for 3.92 levelsmctsahead of Technical & Vocational Skills by 0 per cent
  • BuildLifelong Learning & Reskilling48 credits for 3.97 levelsmcts_fill
  • BuildDigital & AI Competence48 credits for 3.01 levelsmcts_fill
  • BuildFoundational Education48 credits for 2.45 levelsmcts_fill
  • BuildAdvanced Education48 credits for 1.95 levelsmcts_fill

Tiers. Human Capital Tier 2 to 1.

The groups that moved most in 2027, and what moved them
Moved mostChangeInvestedDecayEventsGraph
Lifelong Learning & Reskilling+0.80+0.800.000.000.00
Technical & Vocational Skills+0.78+0.780.000.000.00
Digital & AI Competence+0.60+0.600.000.000.00
Foundational Education+0.49+0.490.000.000.00
Advanced Education+0.39+0.390.000.000.00