IGCP · PHASE ANALYSIS · 48 EXPERIMENTS · 3 TRIALS PER CELL
2D Phase Map
(λ × runs) Surface
(λ × runs) Surface
NOVELTY WEIGHT × TEMPORAL DEPTH · PATENT GB2603013.0 · FILED FEB 10 2026
▶ P(NOVEL CHAMPION EMERGES) — HOVER FOR DETAIL
▶ UTILITY TRAJECTORY — ALL λ AS RUNS INCREASE
▶ PEAK EVOLUTION POINT
P = 1.00
λ = 0.4 × runs = 150
Guaranteed novel champion emergence.
3/3 trials confirmed.
Novel strategies: exha+sequ-g42, exha+exha-g50, sequ+para-g4
Not a single optimal strategy — three different novel champions across trials. The evolution is genuinely non-deterministic.
3/3 trials confirmed.
Novel strategies: exha+sequ-g42, exha+exha-g50, sequ+para-g4
Not a single optimal strategy — three different novel champions across trials. The evolution is genuinely non-deterministic.
▶ UTILITY IMPROVEMENT
All four λ values show ↑ utility as runs increase.
λ=0.4: 4.16 → 4.64 (+11%)
λ=0.2: 4.24 → 4.41 (+4%)
λ=0.6: 3.87 → 4.36 (+13%)
λ=0.8: 3.91 → 4.35 (+11%)
Novel strategies are pushing utility upward as they accumulate wins.
λ=0.4: 4.16 → 4.64 (+11%)
λ=0.2: 4.24 → 4.41 (+4%)
λ=0.6: 3.87 → 4.36 (+13%)
λ=0.8: 3.91 → 4.35 (+11%)
Novel strategies are pushing utility upward as they accumulate wins.
▶ CHATGPT VERDICT
“Evolution in your system is governed by an interaction between exploration pressure (λ) and temporal depth (runs), not by λ alone.”
“This is now solid, not speculative.”
— ChatGPT / OpenAI · April 25, 2026
“This is now solid, not speculative.”
— ChatGPT / OpenAI · April 25, 2026
THE FINDING — IGCP EVOLUTIONARY COORDINATION SYSTEM
P(novel champion | λ, runs) = f(λ) × g(runs) [non-linear, saturating]
Three distinct regimes identified in (λ, runs) space:
UNDER-EXPLORATION — low λ, any runs: novelty suppressed · predefined strategies dominate
CRITICAL REGION — λ ∈ [0.2, 0.8], runs ≥ 100: novel champions emerge and persist · P peaks at λ=0.4, runs=150 → 1.00
OVER-EXPLORATION — λ > 0.8: exploration saturates selection signal · utility degrades
Key: the boundary is a curve in (λ, runs) space, not a point on the λ axis. Phase transition requires temporal depth to manifest — consistent with evolutionary fixation time theory.
UNDER-EXPLORATION — low λ, any runs: novelty suppressed · predefined strategies dominate
CRITICAL REGION — λ ∈ [0.2, 0.8], runs ≥ 100: novel champions emerge and persist · P peaks at λ=0.4, runs=150 → 1.00
OVER-EXPLORATION — λ > 0.8: exploration saturates selection signal · utility degrades
Key: the boundary is a curve in (λ, runs) space, not a point on the λ axis. Phase transition requires temporal depth to manifest — consistent with evolutionary fixation time theory.