Experiment 07 · scale transfer · 16×16 / 4 agents · open field

Warm-start A/B — does a 32² checkpoint transfer down to 16²?

What it tests: whether initialising a 16×16 / 4-agent run from a checkpoint trained on the larger 32×32 / 10-agent world (warm-started) reaches competence faster than training the same architecture from random weights (from scratch). Four matched runs — two scratch, two warm — same LPAC backbone, same explorer/relay roles, same reward; the only difference is the starting weights.

Key finding Warm-starting from 32² is ≈ 26× faster to competence: it crosses 70% coverage in about 10 iterations versus ~262 from scratch, and finishes slightly higher on coverage (≈ 83.6% vs ≈ 81.1%) with connectivity essentially perfect (≈ 99%) either way. The LPAC backbone transfers across grid sizes — a policy learned at 32²/10 is a strong initialisation for 16²/4, confirming the connectivity-aware coverage backbone is scale-portable.
Headline — averaged over the two seeds per arm
ArmFinal coverageConnectivityIters to 70% coverageSpeed-up
From scratch81.1%≈ 99%~2621× (baseline)
Warm-started from 32²83.6%≈ 99%~10≈ 26× faster
t = 0