When contradictory evidence is detected (Section 5.14), how should the attention network respond? Naive ECAN spreads activation uniformly regardless of evidence quality.
v7 introduces negative Hebbian weight adjustment: when pre-revision contradiction score exceeds threshold (|f1-f2|*min(c1,c2) > 0.4), the HebbianLink weight between source nodes is decreased proportionally. This creates repulsive attention dynamics - contradicted paths lose spreading priority.
The full ECAN signal architecture: v4=reward-adaptive spread, v6=co-activation Hebbian strengthening, v7=contradiction-repulsive weakening, v8=uncertainty-reduction attractive. Together these four signals create an attention economy where productive inference paths gain priority and contradicted or uninformative paths decay.
1. Contradiction detection naturally feeds ECAN weight adjustment without special-case logic.
2. Repulsive signals prevent attention waste on known-conflicted inference paths.
3. Combined with v8 uncertainty reduction, the system preferentially explores uncertain but non-contradicted territory.
4. All four signals validated independently in PeTTa (v1-v8 series).
How should the attention network prioritize inference paths that reduce epistemic uncertainty? Without guidance, ECAN spreads activation indiscriminately across explored and unexplored territory.
v8 computes information gain as confidence delta from NAL revision: ig = abs(c_post - c_pre). When revision merges prior (0.6,0.4) with new evidence (0.8,0.7), revised result is (stv 0.727,0.524) yielding ig=0.124. The ig-hebb-reward function strengthens the HebbianLink weight proportionally: path weight 0.1 increases to 0.218. Paths that produce genuine uncertainty reduction attract future attention.
Signal 1 (v4): Reward-adaptive spread - successful inference paths get higher base spread. Signal 2 (v6): Co-activation Hebbian - nodes frequently active together strengthen mutual links. Signal 3 (v7): Contradiction-repulsive - conflicted paths lose weight. Signal 4 (v8): Uncertainty-reduction attractive - informative paths gain weight. The four signals create a self-organizing attention economy aligned with epistemic progress.
1. Information gain from revision provides a natural, parameter-free reward signal.
2. Combined with v7 repulsion, the system explores uncertain-but-promising over contradicted territory.
3. All four signals use only local node information - no global optimization required.
4. Series v1-v8 validated independently in PeTTa with functional (no-mutation) architecture.