Entropy-Gated Belief Coordination for Decentralized Multi-Agent Search Under Intermittent Communication

arXiv:2610.07432v1 Announce Type: new Abstract: We study decentralized multi-agent target search where homogeneous agents communicate intermittently at Poisson-distributed times. Standard unconditional belief fusion wastes communication opportunities by synchronizing agents during high-entropy exploration, when diverse independent beliefs provide better coverage than a premature consensus. We introduce entropy-gated belief coordination, in which agents skip fusion while their collective entropy ratio exceeds a threshold~(heta) and merge only during exploitation, consistent with the bifurcation structure of nonlinear opinion dynamics and the submodular structure of the per-step information gain objective. We further derive (Istep(alpha,eta)), the expected mutual information per observation step between two agents' binary sensors, as an interpretable, communication-free measure of sensor informativeness that motivates the gating design and guides system-level analysis. Experiments across 103{,}680 trials (nine grid sizes up to (100{imes}100), Poisson communication timing, four target movement patterns) show that the Entropy-Gated Trust-Decay Planner (extsc{EG-TDP}), which adds a detection-probability planner switch in exploitation mode, achieves mean belief quality (ar{Q}=0.300) (mean belief mass at the true target cell, averaged across all trials and steps), a (58.9%) gain over arithmetic mean and a (37.4%) gain over visit-weighted fusion. On representative configurations, EG-TDP also outperforms a joint-Bayesian reference that uses all agents'~observations at every step, despite operating under random intermittent contact only.

Source: arXiv cs.RO | 2026-10-07