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Exploiting elementary cellular automata (ECAs) as reservoirs is no exception. Recent studies have shown that the RC implemented by asynchronously tuned ECAs (AT_ECAs) has an advantage of enhancing the learning ability to identify multiple patterns, suggesting effects of critical spacetime patterns that the AT_ECAs create in a wide range of transition rules. However, the generalization capability of the AT_ECA-based RC remains unclear. This study evaluated the generalization performance of the AT_ECA-based RC using the temporal parity task in comparison with the ECA-based RC. We found that the AT_ECA-based RC demonstrated higher performance than ECA-based RC in most rules. This might have been a result of critical behaviors that the AT_ECAs universally generate with different mechanisms from the ECAs.<\/jats:p>","DOI":"10.1007\/s10015-025-01045-x","type":"journal-article","created":{"date-parts":[[2025,7,18]],"date-time":"2025-07-18T08:26:15Z","timestamp":1752827175000},"page":"77-82","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Generalization performance of reservoir computing implemented by asynchronously tuned elementary cellular automaton on parity task"],"prefix":"10.1007","volume":"31","author":[{"given":"Kota","family":"Nakada","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kengo","family":"Takahashi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daisuke","family":"Uragami","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ramon","family":"Alonso-Sanz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrew","family":"Adamatzky","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuta","family":"Nishiyama","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,18]]},"reference":[{"key":"1045_CR1","unstructured":"Jaeger H (2001) The \u201cecho state\u201d approach to analysing and training recurrent neural networks-with an erratum note. 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