Abstract
The Distributed Agent Networks Integrated Efficiency Layer (DANIEL) is a token-free, hardware-agnostic framework for distributed autonomous AI agents that replaces symbolic communication with a three-layer, analog-modeled mathematical system. The framework utilizes phase-matrix integration to execute scalar consensus loops via trigonometric wave equations. Security is enforced by a passive, non-linear activation gate that leverages input gradient vectors to dynamically harden against high-amplitude adversarial prompt injections. Network state synchronization is maintained across a decentralized peer-to-peer mesh mapped onto a continuous toroidal ring topology, employing a rolling average vortex matrix to passively filter localized agent hallucinations and single-node failures. This integrated architecture removes text-token serialization overhead, eliminates application-layer firewall latency, and prevents centralized processing bottlenecks in distributed agentic systems.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Eckes, Christopher L., "Defensive Specifications Disclosure: Token-Free, Non-Linear Boundary, and Wave-Interference Based Architecture for Distributed Autonomous AI Agent Frameworks", Technical Disclosure Commons, (July 06, 2026)
https://www.tdcommons.org/dpubs_series/10807