Energy-Based Stability Control for Suppressing Memory Poisoning in Multi-Agent Collaborative Systems
DOI:
https://doi.org/10.66238/fsrma51Keywords:
Multi-agent systems, memory poisoning, stability control, Lyapunov analysis, collaborative robustness, dynamic systemsAbstract
Memory poisoning can destabilize collaborative agent dynamics by introducing divergent update trajectories. This study models system stability using a Lyapunov-inspired energy function defined over collective memory states. An adaptive damping mechanism constrains updates that increase system energy beyond predefined bounds. The method was tested on a 150-agent cooperative optimization benchmark across 5,000 iterations. Under a 20% poisoning scenario, baseline systems exhibited energy divergence in 64.5% of runs. Energy-controlled systems reduced divergence probability to 17.8% and maintained 91.6% of nominal task efficiency. Energy-based stability control offers a control-theoretic approach to suppress contamination-induced instability.
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