Autonomous objective with exploration and repetition terms

Read the equation

The objective combines task value, exploration, an adaptive parameter term, conflict and resource penalties, entropy regularization and a repetition penalty. If this J is maximized, the plus entropy term encourages diversity when it represents positive entropy.

Its role in the build

Unified AGI Equation System

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 J 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

• The source does not explicitly give an argmax, numerical weights, a definition of adaptive_theta_term, or the sign convention used for entropy. Those details determine actual behavior.

Original context

Unified AGI Equation System: The objective combines task value, exploration, an adaptive parameter term, conflict and resource penalties, entropy regularization and a repetition penalty. If this J is maximized, the plus entropy term encourages diversity when it represents positive entropy.

J = base_objective + exploration_bonus + adaptive_theta_term − conflict_penalty − resource_penalty + entropy_regularization − repetition_penalty

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