Read the equation
Updates an aspect-level controller or environment state using the previous state and messages from layers. The transition function is named but not fully supplied in the shorthand.
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
Read E^{(a)}_{next} as the quantity being defined or updated by this relation.
Substitute the source-defined variables or recorded values and follow the displayed arithmetic and indexing exactly.
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
Read the surrounding source passage
• Then C^{(a)} is fed back into the environment description for the next step.
Update the actual aspect:
E^{(a)}_{\text{next}} = G_a\big(E^{(a)}_{\text{current}}, C^{(a)}\big)
So:
• Layers talk to each other through shared aspect contexts C^{(a)}.
• Every layer reads the same updated aspect when it re-runs its optimization.
This is your “neuron conversation across all aspects of each environment,” in math form.Exact original notation
E^{(a)}_{\text{next}} = G_a\big(E^{(a)}_{\text{current}}, C^{(a)}\big)Related builds
Sources & provenance
E^{(a)}_{\text{next}} = G_a\big(E^{(a)}_{\text{current}}, C^{(a)}\big)
E^{(a)}_{\text{next}} = G_a\big(E^{(a)}_{\text{current}}, C^{(a)}\big)