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We consider a problem where autonomous agents enter a dynamic and unknownenvironment described by a network of weighted arcs. These agents move withinthe network from node to node according to a decentralized policy using onlylocal information, with the goal of finding a path to an unknown sink node toleave the network. This policy makes each agent move to some adjacent node orstop at the current node. The transition along an arc is allowed or deniedbased on a threshold mechanism that takes into account the number of agentsalready accumulated in the arc's end nodes and the arc's weight. We show thatthis policy ensures path-length optimality in the sense that, in a finite time,all new agents entering the network reach the closer sinks by the shortestpaths. Our approach is later extended to support constraints on the paths thatagents can follow.

An agent-based decentralized threshold policy finding the constrained shortest paths