The plasmodium of the slime mold Physarum polycephalum, a large amoeboid organism, displays remarkable intelligent behaviors such as solving mazes, shuttle streaming and event anticipation. These amoeboid behaviors are results of the dynamics of the viscoelastic protoplasm and its biochemical rhythms. Having inspired by the intelligence shown by this primitive organism without a nerve system to solve mazes, we proposed mathematical models to mimic the intelligent foraging behavior that can be used to find the shortest path between two points of a graph. In result, we found that the convergence of the proposed two versions, Physarum Optimization with Shuttle Streaming (POSS) and POSS with mutation, are 40-11650 times faster when compared with the currently available Physarum Solver (PS) method and the results obtained are comparable.
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