Graph-Based Orchestration of Heterogeneous AI Models: A Control Node Approach to Composite Intelligence

arXiv15 octombrie 20261 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2610.19136v1 Announce Type: new Abstract: We present a graph-based framework for Composite AI systems that integrate multiple AI techniques to address complex problems. We describe an architecture using specialized control nodes to orchestrate diverse models including planning, machine learning, constraint programming, and large language models. The system employs directed acyclic graphs and behavior trees to manage model relationships and execution sequencing. Our methodology encompasses data connectors, computational services, and a containerized deployment framework supporting hierarchical, sequential, and concurrent model composition patterns. Through case studies, we demonstrate how this architecture enables the creation of composite systems that leverage the strengths of multiple AI techniques within a unified operational schema, overcoming the limitations of single-model approaches.

Abstract:We present a graph-based framework for Composite AI systems that integrate multiple AI techniques to address complex problems. We describe an architecture using specialized control nodes to orchestrate diverse models including planning, machine learning, constraint programming, and large language models. The system employs directed acyclic graphs and behavior trees to manage model relationships and execution sequencing. Our methodology encompasses data connectors, computational services, and a containerized deployment framework supporting hierarchical, sequential, and concurrent model composition patterns. Through case studies, we demonstrate how this architecture enables the creation of composite systems that leverage the strengths of multiple AI techniques within a unified operational schema, overcoming the limitations of single-model approaches.

8 pages, 4 figures, Citation: G. Michael Youngblood, Filip Dvořák, Slavo Švancár, Tomáš Balyo, Michal Ficek, and Martin Dousek. Graph-Based Orchestration of Heterogeneous AI Models: A Control Node Approach to Composite Intelligence. IJCAI Workshop on Composite AI (CompAI). 2025

Artificial Intelligence (cs.AI)

arXiv:2610.19136 [cs.AI]

(or arXiv:2610.19136v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2610.19136 arXiv-issued DOI via DataCite (pending registration)

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Graph-Based Orchestration of Heterogeneous AI Models: A Control Node Approach to Composite Intelligence

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