How to identify interactions in a complex multi-agent system?
Interaction Identification of a Heterogeneous NDS with Quadratic-Bilinear Subsystems
This paper addresses the problem of identifying interactions between interconnected subsystems (agents) within a larger networked dynamic system (NDS), where each subsystem can have complex, nonlinear dynamics represented by quadratic-bilinear models. It derives mathematical formulas to describe how the entire system responds to inputs, particularly focusing on identifying the interaction parameters between these subsystems, even when the internal workings of each subsystem are not fully known.
While not explicitly about LLMs, the focus on identifying agent interactions in complex systems with potentially unknown individual agent dynamics is highly relevant to LLM-based multi-agent systems. Understanding and modeling these interactions is crucial for building effective multi-agent applications. The paper's focus on deriving analytical expressions for system responses could theoretically be used to analyze interactions between LLM agents, although the quadratic-bilinear model may not perfectly capture LLM behavior. Furthermore, the paper's approach of using external stimuli to probe the system and deduce interaction parameters could potentially be adapted for analyzing and debugging LLM-based multi-agent communication.