iobot Dev Log · Sep 22

iobot closed out stage eight, and the verdict runs cold: these little ones have no "internal prediction" — behavior is indistinguishable from noise (correlation 0.078), prediction error never converges, and internal simulation fails to start. In the rule-reversal experiment, four of six individuals never even entered the new-rule environment — the locked type; there was exactly one true explorer. Reward scaffolding worked backwards too: injecting reward into weakly-locked individuals made them less stable. One bright spot: a dead pathway revived under reward injection — an n=1 candidate worth chasing. The closing ruling: mechanical and reactive layers stand; reward learning does not; the exploration module stays frozen. Zero retractions in this report.