Optimal random search using limited spatial memory
Lévy walks are known to be efficient movements because Lévy walkers search wide areas while restricting returns to previously visited sites. A self-avoiding walk (SAW) is a series of moves on a lattice that visit the same place only once. As such, SAWs can also be effective search algorithms. Howeve...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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The Royal Society
2018-01-01
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| Series: | Royal Society Open Science |
| Subjects: | |
| Online Access: | https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.171057 |
| _version_ | 1819006302397923328 |
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| author | Tomoko Sakiyama Yukio-Pegio Gunji |
| author_facet | Tomoko Sakiyama Yukio-Pegio Gunji |
| author_sort | Tomoko Sakiyama |
| collection | DOAJ |
| description | Lévy walks are known to be efficient movements because Lévy walkers search wide areas while restricting returns to previously visited sites. A self-avoiding walk (SAW) is a series of moves on a lattice that visit the same place only once. As such, SAWs can also be effective search algorithms. However, it is not realistic that foragers memorize many visited positions for a long time. In this work, we investigated whether foragers performed optimal searches when having limited memory. The agent in our model followed SAWs to some extent by memorizing and avoiding visited places. However, the agent lost its memory after a while. In that situation, the agent changed its reactions to visited patches by considering global trail patterns based on local memorized information. As a result, we succeeded in making the agent occasionally produce ballistic walks related to power-law tailed movements across some ranges. |
| first_indexed | 2024-12-21T00:06:31Z |
| format | Article |
| id | doaj.art-297a516816124ddfbc4155b16c969060 |
| institution | Directory Open Access Journal |
| issn | 2054-5703 |
| language | English |
| last_indexed | 2024-12-21T00:06:31Z |
| publishDate | 2018-01-01 |
| publisher | The Royal Society |
| record_format | Article |
| series | Royal Society Open Science |
| spelling | doaj.art-297a516816124ddfbc4155b16c9690602022-12-21T19:22:27ZengThe Royal SocietyRoyal Society Open Science2054-57032018-01-015310.1098/rsos.171057171057Optimal random search using limited spatial memoryTomoko SakiyamaYukio-Pegio GunjiLévy walks are known to be efficient movements because Lévy walkers search wide areas while restricting returns to previously visited sites. A self-avoiding walk (SAW) is a series of moves on a lattice that visit the same place only once. As such, SAWs can also be effective search algorithms. However, it is not realistic that foragers memorize many visited positions for a long time. In this work, we investigated whether foragers performed optimal searches when having limited memory. The agent in our model followed SAWs to some extent by memorizing and avoiding visited places. However, the agent lost its memory after a while. In that situation, the agent changed its reactions to visited patches by considering global trail patterns based on local memorized information. As a result, we succeeded in making the agent occasionally produce ballistic walks related to power-law tailed movements across some ranges.https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.171057movement strategypower lawforaging |
| spellingShingle | Tomoko Sakiyama Yukio-Pegio Gunji Optimal random search using limited spatial memory Royal Society Open Science movement strategy power law foraging |
| title | Optimal random search using limited spatial memory |
| title_full | Optimal random search using limited spatial memory |
| title_fullStr | Optimal random search using limited spatial memory |
| title_full_unstemmed | Optimal random search using limited spatial memory |
| title_short | Optimal random search using limited spatial memory |
| title_sort | optimal random search using limited spatial memory |
| topic | movement strategy power law foraging |
| url | https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.171057 |
| work_keys_str_mv | AT tomokosakiyama optimalrandomsearchusinglimitedspatialmemory AT yukiopegiogunji optimalrandomsearchusinglimitedspatialmemory |