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      Solving NP-Hard Problems with <italic>Physarum</italic>-Based Ant Colony System

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          Ant colony system: a cooperative learning approach to the traveling salesman problem

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            Ant colony optimization: a new meta-heuristic

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              A mathematical model for adaptive transport network in path finding by true slime mold.

              We describe here a mathematical model of the adaptive dynamics of a transport network of the true slime mold Physarum polycephalum, an amoeboid organism that exhibits path-finding behavior in a maze. This organism possesses a network of tubular elements, by means of which nutrients and signals circulate through the plasmodium. When the organism is put in a maze, the network changes its shape to connect two exits by the shortest path. This process of path-finding is attributed to an underlying physiological mechanism: a tube thickens as the flux through it increases. The experimental evidence for this is, however, only qualitative. We constructed a mathematical model of the general form of the tube dynamics. Our model contains a key parameter corresponding to the extent of the feedback regulation between the thickness of a tube and the flux through it. We demonstrate the dependence of the behavior of the model on this parameter.
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                Author and article information

                Journal
                IEEE/ACM Transactions on Computational Biology and Bioinformatics
                IEEE/ACM Trans. Comput. Biol. and Bioinf.
                Institute of Electrical and Electronics Engineers (IEEE)
                1545-5963
                1557-9964
                2374-0043
                January 1 2017
                January 1 2017
                : 14
                : 1
                : 108-120
                Article
                10.1109/TCBB.2015.2462349
                d4f289d1-93af-4417-80b6-4515999d30c7
                © 2017
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