/closest-worlds

name: closest-worlds
description: 'Strategy: Lewis Possible Worlds — find the minimal change to reality
  that would flip the conclusion, measuring how close the nearest world where the
  conclusion fails.'
type: strategy
tactics:
- minimal-change-search
- systematic-factor-ablation
dependencies:
  tactics:
  - minimal-change-search
  - systematic-factor-ablation
  sops:
  - causal-claim-extraction
  - counterfactual-scenario-construction
  - factor-enumeration
  - flip-point-detection
  - fragility-measurement
  - load-bearing-identification

Closest Worlds Strategy

Lewis semantics: evaluate counterfactuals by finding the nearest possible world where the antecedent holds and checking whether the consequent follows.

Method

1. **causal-claim-extraction** identifies the conclusion and its supporting factors 2. **factor-enumeration** maps the space of possible changes 3. **flip-point-detection** searches for minimal changes that flip the conclusion 4. **counterfactual-scenario-construction** builds the nearest world where conclusion fails 5. **fragility-measurement** computes distance from actuality to flip-point 6. **load-bearing-identification** ranks factors by proximity to flip

Budget Table

| Parameter | S | M | L | |---|---|---|---| | Change candidates explored | 5 | 12 | 25 | | Flip-point searches | 3 | 8 | 15 | | World-distance comparisons | 3 | 6 | 12 |

Orchestration

causal-claim-extraction → factor-enumeration
→ [generate change candidates]:
    flip-point-detection (binary search for minimal flip)
    → counterfactual-scenario-construction (build nearest world)
    → fragility-measurement (compute distance)
→ load-bearing-identification (rank by proximity)

Subagents

• causal-claim-extraction (conclusion identification)
• factor-enumeration (change space mapping)
• flip-point-detection (minimal flip search)
• counterfactual-scenario-construction (world building)
• fragility-measurement (distance computation)
• load-bearing-identification (proximity ranking)

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Available Tactics

Optional, no fixed order; the final leaf is always a sop.

| Tactic | When to use | | --- | --- | | minimal-change-search | Tactic: Generate candidate changes, detect flip-points where conclusion reverses, measure fragility as distance to nearest flip. | | systematic-factor-ablation | Tactic: List all factors, remove one at a time, assess conclusion stability, rank factors by load-bearing importance. |

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

| SOP | When to use | | --- | --- | | causal-claim-extraction | Extract all causal claims (X causes Y, X leads to Y, X enables Y) from an artifact, producing a structured list of cause-effect pairs. | | counterfactual-scenario-construction | Construct precise, internally consistent counterfactual scenarios where specified factors are altered, then reason about the resulting conclusion. | | factor-enumeration | List all key factors, conditions, and assumptions that support or enable the artifact's conclusion. | | flip-point-detection | Find the minimal change magnitude along a dimension that causes the conclusion to flip from true to false. | | fragility-measurement | Compute a fragility index from flip-point distances and degradation scores, summarizing how robust the conclusion is. | | load-bearing-identification | Identify which factors are "load-bearing walls" — factors whose removal would collapse the conclusion. |

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