Cognitive RPA Swarms: Leveraging ML Driven Collective Intelligence for Decentralized Process Automation

Abstract

Cognitive Robotic Process Automation (RPA) swarms represent a transformative leap in automation, merging machine learning (ML) with swarm intelligence to enable decentralized, self-organizing systems. This paper introduces a framework where autonomous agents collaboratively optimize workflows through ML-driven collective intelligence, addressing scalability, adaptability, and resilience challenges in traditional RPA. By integrating neural-symbolic task interpretation, federated learning, and stigmergic coordination, the system achieves a 40% improvement in process efficiency and 92% fault tolerance in simulated environments. Theoretical advancements and empirical validation underscore the potential of cognitive RPA swarms to redefine enterprise automation.