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A3: PS+ surfaces all 30 raw sensates but only the 2 most salient priors (L3 ranked-top-2); evaluate_reality arguments carries top-2 only. A6: top-X convictions rationale — the conviction list can be massive. A1 step 2: all 30 sensates + 2 most salient priors; note the asymmetry (fixed-30 surfaces whole; unbounded prior/conviction lists are ranked). https://claude.ai/code/session_015hmgREHNsxYCuim33yUF2c
3.1 KiB
3.1 KiB
A6 — Eth-Int (Ethical Integrity) driver
1. Component
Driver 3: character as an economic constraint field — a cost-map, not a moral oracle. Produces the E-cost of responding to reality: alignment discounts, antithetical penalties, conviction hardening.
2. Status / certainty
Structure WORKING (driver_ethical_integrity.R, 87 L); numbers DISOWNED (body §5). Per arch §6 it is
not a stored stratum — a memory-derivative (entries with memory-weighted shifting numerics).
3. Language & location
R · src/endocrine/driver_ethical_integrity.R (+ test_ethical_integrity.R). Its state = the
Conviction array (A7).
4. Does / does-not
- Does: evaluate a trajectory's E-cost (alignment discount × antithesis penalty × compromise); harden convictions upheld under load; treat middle-ground as its own trajectory; surface the top X convictions (by strength) into the agent's slot — not the whole array (Anja: the conviction list can be massive, so it must be ranked & truncated; A1 step 3 / input-slot).
- Does-not: assert moral truth, or persist itself as a stratum (it derives from memory; see A7/E2).
5. Interface contract
evaluate_trajectory_costs(convictions, action_tags, alignment_tags, base_energy, compromise_factor) -> total_cost(penalty exponential in conviction; discount exponential; compromise = partial penalty).enforce_conviction(convictions, chosen_alignment_tags, load_factor) -> convictions'(hardening ∝ load, diminishing toward 1.0).top_convictions(convictions, x) -> [..]— the top X by strength, the only ones surfaced to the slot (Anja). X is C1 (see §10).- Reads/writes the conviction array (A7). Emits
eth_penaltyconsumed by Energy (A2).
6. Dependencies & stubs
A7 conviction array — stub: a flat list {id, conviction, antithesis} (today's shape). Energy (A2)
consumes its penalty — stub: return the scalar. Testable today against the flat array.
7. Invariants / laws (numbers C1 until tested)
- L1 (C4): antithetical action → cost rises exponentially in conviction; multiple violations add (can exceed E capacity → physically impossible).
- L2 (C4): alignment → exponential discount ("flow state").
- L3 (C4): middle-ground is a separate trajectory with partial penalties to both poles, weighed against the polar options.
- L4 (C4): conviction hardens under load; G1 stress raises the shift-rate (A7).
- L5 (C1): all k's (penalty/discount/compromise) — refit invariants-first.
8. Build steps
- Lock L1–L4 as tests (extend
test_ethical_integrity.R). 2. Refit the k's — drop old k_penalty=5 / k_discount=5. 3. Migrate state to the A7 conviction array (isomorphy tags + shift-rates). 4. Wire G1.
9. Tests
Rscript src/endocrine/test_ethical_integrity.R.
10. Open items
- The k constants (C1). The middle-ground compromise scaling (C1).
- X — how many convictions surface to the slot (C1; ranked by strength).
- Exact "memory-derivative" derivation (how convictions are computed from memory) — ties to A7/E2.