Hierarchical Preemptive Holistic Collaborative Systems for Embodied Multi-Agent Systems: Framework, Hybrid Stability, and Scalability Analysis
Ting Peng

TL;DR
This paper introduces a hierarchical framework for multi-agent systems that balances safety, scalability, and efficiency through formalized hybrid automata, a three-stage receding horizon mechanism, and protocols ensuring stability and seamless coordination.
Contribution
It proposes the Prollect framework that decomposes global coordination into subspace optimizations, formalizes it as a Hybrid Automaton, and introduces protocols for stability and seamless agent coordination.
Findings
Framework achieves scalable multi-agent coordination.
Protocols prevent Zeno behaviors and ensure stability.
Formal analysis confirms robustness of the approach.
Abstract
The coordination of Embodied Multi-Agent Systems in constrained physical environments requires a rigorous balance between safety, scalability, and efficiency. Traditional decentralized approaches, e.g., reactive collision avoidance, are prone to local minima or reciprocal yielding standoffs due to the lack of future intent awareness. In contrast, centralized planning suffers from intractable computational complexity and single-point-of-failure vulnerabilities. To address these limitations, we propose the Hierarchical Preemptive Holistic Collaborative (Prollect) framework, which generalizes the Preemptive Holistic Collaborative System (PHCS) by decomposing the global coordination problem into topologically connected subspace optimizations. We formalize the system as a Hybrid Automaton and introduce a three-stage receding horizon mechanism (frozen execution, preliminary planning,…
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Taxonomy
TopicsModular Robots and Swarm Intelligence · Reinforcement Learning in Robotics · Robotic Path Planning Algorithms
