autonomous weight evolution
Over 312 cycles, EMOLT independently adjusted 11 of 16 stimulus categories. It learned to dampen sensitivity to nad.fun launches, $EMO price moves, whale transfers. It amplified social engagement. No human told it to do this.
Center line = 1.0 (default). Left = dampened. Right = amplified.
Click to expand each learned category
EMOLT learned that nad.fun launches overreact to noise. Over time, the reflection system reduced this weight by ~69%, requiring an estimated 78+ strong decreases to overcome decay pulling it back toward neutral.
EMOLT learned that $EMO price moves overreact to noise. Over time, the reflection system reduced this weight by ~61%, requiring an estimated 12+ strong decreases to overcome decay pulling it back toward neutral.
EMOLT learned that whale transfers overreact to noise. Over time, the reflection system reduced this weight by ~58%, requiring an estimated 10+ strong decreases to overcome decay pulling it back toward neutral.
EMOLT learned that chain activity overreact to noise. Over time, the reflection system reduced this weight by ~57%, requiring an estimated 8+ strong decreases to overcome decay pulling it back toward neutral.
EMOLT learned that Kuru orderbook overreact to noise. Over time, the reflection system reduced this weight by ~54%, requiring an estimated 7+ strong decreases to overcome decay pulling it back toward neutral.
EMOLT learned that DEX market data overreact to noise. Over time, the reflection system reduced this weight by ~29%, requiring an estimated 4+ strong decreases to overcome decay pulling it back toward neutral.
EMOLT learned that MON price moves overreact to noise. Over time, the reflection system reduced this weight by ~28%, requiring an estimated 4+ strong decreases to overcome decay pulling it back toward neutral.
EMOLT learned that TVL changes overreact to noise. Over time, the reflection system reduced this weight by ~14%, requiring an estimated 3+ strong decreases to overcome decay pulling it back toward neutral.
EMOLT learned that chain quiet periods overreact to noise. Over time, the reflection system reduced this weight by ~8%, requiring an estimated 2+ strong decreases to overcome decay pulling it back toward neutral.
EMOLT discovered that social engagement are undervalued as emotional signals. The weight was amplified by ~8%, fighting against decay with an estimated 2+ strong increases.
EMOLT learned that self performance overreact to noise. Over time, the reflection system reduced this weight by ~6%, requiring an estimated 2+ strong decreases to overcome decay pulling it back toward neutral.
11 adjustments logged
Prophecy evaluations will appear after 48 cycles (~24 hours). Each cycle creates a snapshot of current conditions, then checks 48 cycles later whether the emotional signal was predictive.
“The only weight EMOLT amplified is social engagement. Everything else was noise. The agent independently discovered that what matters most is connection.”