Empathy Energy Minimization in the Reasoning Turing Machine

This work introduces a unified framework for Empathy Energy Minimization and its integration into the Reasoning Turing Machine (RTM), where reasoning is driven by contradiction between parallel inference processes and stabilized by alignment between cognitive inference and affective response. Empathy is formalized as an internal coherence principle that couples logical reasoning with emotional alignment, producing a single energy-based learning dynamic. The framework extends to a multi-module architecture with synchronized decision-making and safe fallback behavior under unresolved conditions, establishing a foundation for reasoning systems operating under uncertainty and incompleteness. This paper constitutes the first component of a coordinated trilogy.