TY - GEN
T1 - A stochastic approach to shortcut bridging in programmable matter
AU - Andrés Arroyo, Marta
AU - Cannon, Sarah
AU - Daymude, Joshua J.
AU - Randall, Dana
AU - Richa, Andrea
N1 - Funding Information:
S. Cannon—Supported in part by NSF DGE-1148903 and a grant from the Simons Foundation (#361047). J.J. Daymude—Supported in part by NSF CCF-1637393. D. Randall—Supported in part by NSF CCF-1637031 and CCF-1526900. A.W. Richa—Supported in part by NSF CCF-1637393 and CCF-1422603.
Publisher Copyright:
© 2017, Springer International Publishing AG.
PY - 2017
Y1 - 2017
N2 - In a self-organizing particle system, an abstraction of programmable matter, simple computational elements called particles with limited memory and communication self-organize to solve system-wide problems of movement, coordination, and configuration. In this paper, we consider stochastic, distributed, local, asynchronous algorithms for “shortcut bridging,” in which particles self-assemble bridges over gaps that simultaneously balance minimizing the length and cost of the bridge. Army ants of the genus Eticon have been observed exhibiting a similar behavior in their foraging trails, dynamically adjusting their bridges to satisfy an efficiency tradeoff using local interactions [1]. Using techniques from Markov chain analysis, we rigorously analyze our algorithm, show it achieves a near-optimal balance between the competing factors of path length and bridge cost, and prove that it exhibits a dependence on the angle of the gap being “shortcut” similar to that of the ant bridges. We also present simulation results that qualitatively compare our algorithm with the army ant bridging behavior. The proposed algorithm demonstrates the robustness of the stochastic approach to algorithms for programmable matter, as it is a surprisingly simple generalization of a stochastic algorithm for compression [2].
AB - In a self-organizing particle system, an abstraction of programmable matter, simple computational elements called particles with limited memory and communication self-organize to solve system-wide problems of movement, coordination, and configuration. In this paper, we consider stochastic, distributed, local, asynchronous algorithms for “shortcut bridging,” in which particles self-assemble bridges over gaps that simultaneously balance minimizing the length and cost of the bridge. Army ants of the genus Eticon have been observed exhibiting a similar behavior in their foraging trails, dynamically adjusting their bridges to satisfy an efficiency tradeoff using local interactions [1]. Using techniques from Markov chain analysis, we rigorously analyze our algorithm, show it achieves a near-optimal balance between the competing factors of path length and bridge cost, and prove that it exhibits a dependence on the angle of the gap being “shortcut” similar to that of the ant bridges. We also present simulation results that qualitatively compare our algorithm with the army ant bridging behavior. The proposed algorithm demonstrates the robustness of the stochastic approach to algorithms for programmable matter, as it is a surprisingly simple generalization of a stochastic algorithm for compression [2].
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U2 - 10.1007/978-3-319-66799-7_9
DO - 10.1007/978-3-319-66799-7_9
M3 - Conference contribution
AN - SCOPUS:85029009287
SN - 9783319667980
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 122
EP - 138
BT - DNA Computing and Molecular Programming - 23rd International Conference, DNA 23, Proceedings
A2 - Brijder, Robert
A2 - Qian, Lulu
PB - Springer Verlag
T2 - 23rd International Conference on DNA Computing and Molecular Programming, DNA 2017
Y2 - 24 September 2017 through 28 September 2017
ER -