How can I build robust distributed estimators in faulty networks?
On the Design of Resilient Distributed Single Time-Scale Estimators: A Graph-Theoretic Approach
This paper proposes a resilient, distributed, single time-scale estimator for interconnected systems, applicable to sensor networks. It uses a graph-theoretic approach to ensure the estimator continues functioning even if some sensors or communication links fail.
Key points for LLM-based multi-agent systems: The distributed approach, where each agent (sensor/LLM) maintains its own estimate and refines it by communicating with neighbors, increases resilience to individual agent failures. The focus on minimizing communication steps is crucial for LLMs due to the potentially high computational cost of their interactions. The graph-theoretic approach for designing robust network topologies offers valuable insights into structuring multi-agent LLM systems for optimal resilience and performance. The concept of observational equivalence, where redundant information from some agents can compensate for the loss of others, could be explored for incorporating redundancy in LLM responses and ensuring reliability despite individual LLM limitations or failures.