Hop-by-hop federation activation propagation

Read the equation

Adds neighboring activation contributions to an agent’s previous-hop activation, weighted by graph edges and coherence. Repeated hops can amplify signals unless the network weights or an additional normalization constrain growth.

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 A_i^{hop} as the quantity being defined or updated by this relation.

2. Substitute the source-defined variables or recorded values and follow the displayed arithmetic and indexing exactly.

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

DISTRIBUTED QUERY
A_i^{hop} = A_i^{hop-1} + Σ w_ij·Φ(C_ij)·A_j^{hop-1}

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A_i^{hop} = A_i^{hop-1} + Σ w_ij·Φ(C_ij)·A_j^{hop-1}

Related builds