The foraging problem asks how a collective of particles with limited computational, communication and movement capabilities can autonomously compress around a food source and disperse when the food is depleted or shifted, which may occur at arbitrary times. We would like the particles to iteratively self-organize, using only local interactions, to correctly gather whenever a food particle remains in a position long enough and search if no food particle has existed recently. Unlike previous approaches, these search and gather phases should be self-induced so as to be indefinitely repeatable as the food evolves, with microscopic changes to the food triggering macroscopic, system-wide phase transitions. We present a stochastic foraging algorithm based on a phase change in the fixed magnetization Ising model from statistical physics: Our algorithm is the first to leverage self-induced phase changes as an algorithmic tool. A key component of our algorithm is a careful token passing mechanism ensuring a dispersion broadcast wave will always outpace a compression wave.
@InProceedings{oh_et_al:LIPIcs.DISC.2022.51, author = {Oh, Shunhao and Randall, Dana and Richa, Andr\'{e}a W.}, title = {{Brief Announcement: Foraging in Particle Systems via Self-Induced Phase Changes}}, booktitle = {36th International Symposium on Distributed Computing (DISC 2022)}, pages = {51:1--51:3}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-255-6}, ISSN = {1868-8969}, year = {2022}, volume = {246}, editor = {Scheideler, Christian}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2022.51}, URN = {urn:nbn:de:0030-drops-172423}, doi = {10.4230/LIPIcs.DISC.2022.51}, annote = {Keywords: Foraging, self-organized particle systems, compression, phase changes} }
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