Toward Interoperable Modulatory Architectures for Modular AI Systems
Executive Summary Toward Interoperable Modulatory Architectures for Modular AI Systems Len Bullard – AIArtistinProcess Motivation Modern AI systems, including world models, reinforcement learners, and multi-agent networks, rely on implicit modulatory mechanisms—attention scaling, gating, normalization, and meta-optimization—to shape learning and behavior. These mechanisms are critical to stability, adaptation, and emergent behavior, yet they are: Embedded within architectures Difficult to inspect or modify Often non-portable across systems This paper proposes an explicit, interoperable framework for describing and manipulating modulatory influences. Key Concept: Modulatory Fields Definition: Continuous influences that bias signal flow without encoding content. Attributes: Scope (local → global), timescale, polarity (facilitative/suppressive/stabilizing), target domain (perception, memory, learning, action). Function: Shape the probability and persist...