Emmanuelle: A Symbolic-Cognitive Agent Grounded in Universal Virtues via the S-Module Architecture

We present the Module S, a symbolic artificial intelligence architecture integrating seven universal virtues as a guiding framework for agent behavior and learning. Grounded in a dynamically updated semantic graph, the model aligns low-level reinforcement learning signals with high-level symbolic states, selected and regulated by virtue-based weighting. Emmanuelle, the resulting system, demonstrates sustained alignment, interpretability, and ethical consistency in environments such as CartPole-v1 and LunarLander-v2. This work introduces a new paradigm of moral symbolic alignment, combining the power of neural agents with a cosmically inspired symbolic backbone.