Derives closed-form solutions for KL-divergence belief merging and a visit-weighted variant, reducing complexity to O(N|S|) and outperforming standard methods in simulations with noisy sensors and long communication gaps.
Cooperative multi-agent target searching: a deep reinforcement learning approach based on parallel hindsight experience replay,
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Robust Multi-Agent Target Tracking in Intermittent Communication Environments via Analytical Belief Merging
Derives closed-form solutions for KL-divergence belief merging and a visit-weighted variant, reducing complexity to O(N|S|) and outperforming standard methods in simulations with noisy sensors and long communication gaps.