Abstract
A technique is described for an integrated simulation framework that uses a distributed agentic topology. Such a framework can address potential limitations where some isolated predictive models in analytical frameworks may not capture complex interdependencies. In this framework, operational entities can be represented by autonomous software agents interconnected by a semantic dependency graph that maps causal relationships. When an agent detects a change in its domain, it may generate and broadcast a probabilistic state vector, which can trigger a chain reaction of cascading recalculations across the network of connected agents. This process allows for the simulation of non-linear operational effects across different domains. The framework can be used to create a synchronized digital model of a complex system, which may facilitate the generation of operational forecasts, remediation guidance, and context-aware insights.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
S, Gunalan; Parinam, Venkata Siddharth; Heera, Mohammad; Tyagi, Achal; and Raghuvanshi, Mohit, "Cascading Predictive Simulation Using a Distributed Agentic Topology", Technical Disclosure Commons, (April 09, 2026)
https://www.tdcommons.org/dpubs_series/9747