Epona aggregation of 80 neuron losses

Read the equation

Feeds the weighted sum of 80 neuron losses, device metrics and policy information into an outer aggregator Φ. Here Φ names an aggregation function; it must not be silently identified with the unity weighting score, golden ratio or IIT Φ.

Terms & definitions

The recovered passage does not supply a separate symbol table. Read the source context for the notation used in this version; familiar letters may carry different meanings in other builds.

How it works

1. Read \mathcal{L}_{Epona} as the quantity being defined or updated by this relation.

2. Adds the indexed contributions. The summation limits determine which components participate.

3. Use this version’s variable definitions and update order. The same symbol may be assigned a different meaning in another build.

Assumptions & limits

Source recovery establishes that the expression appears in this record. Its mathematical validity, implementation behavior, and interpretation must be assessed separately. See the linked source and research notes for the checks available for this version.

Original context

3. Combined Epona–Rhiannon equation (compact)

You can write a compact two-level objective:

\mathcal{L}_{\text{Epona}} =
\Phi\Big(
\sum_{i=1}^{80} \omega_i L_i^\*(S',D'; U_i, E_{\ell(i)}),
\; \text{device metrics},\; \text{policy}
\Big)
•	Outer Φ: Epona’s aggregator
•	Inner sum: full Rhiannon 80-neuron derived losses
•	Each Lᵢ^*: derived from the single global L^* you started with.

This is the complete, layered, measurement-consistent picture:
•	one global equation
•	derived per layer
•	derived per neuron
•	instantiated per task/environment
•	supervised and weighted by Epona.

\mathcal{L}_{\text{Epona}} =
\Phi\Big(
\sum_{i=1}^{80} \omega_i L_i^\*(S',D'; U_i, E_{\ell(i)}),
\; \text{device metrics},\; \text{policy}
\Big)
•	Outer Φ: Epona’s aggregator
•	Inner sum: full Rhiannon 80-neuron derived losses
•	Each Lᵢ^*: derived from the single global L^* you started with.

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