{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T15:22:35Z","timestamp":1758640955728,"version":"3.44.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686110","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T00:00:00Z","timestamp":1758499200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9,22]]},"abstract":"<jats:p>Despite addressing dynamic learning scenarios, the Continual Learning paradigm is still an evolving field, with no consensus on a definitive methodology among the numerous approaches proposed. In this study, we reflect upon possible novel perspectives about the learning process itself, posing a few questions: how does information get structured in models\u2019 parameters? what if memory and oblivion were two faces of the same coin? therefore, could we conceive a network capable of both learning and forgetting continuously? We put forward that information be distributed as a harmony, meaning that there should be some degree of consonance in the data for the continuous learning process to succeed. Provided that, Continual Learning might be possible, say, as a variation on the theme, possibly deeming optimization as a kind of orchestration, even among various agents. We encourage the enhancement of this framework, where current brute-force monolithic models would be surpassed in favor of more efficient agents, capable of evolving dynamically from their interactions.<\/jats:p>","DOI":"10.3233\/faia250656","type":"book-chapter","created":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T14:37:12Z","timestamp":1758638232000},"source":"Crossref","is-referenced-by-count":0,"title":["Too Many Butterflies from One Chrysalis. Continual Learning, Continual Forgetting and the Harmonic Flow of Information"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-2896-5900","authenticated-orcid":false,"given":"Elio","family":"Grande","sequence":"first","affiliation":[{"name":"University of Pisa"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5428-156X","authenticated-orcid":false,"given":"Luigi","family":"Quarantiello","sequence":"additional","affiliation":[{"name":"University of Pisa"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","HHAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA250656","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T14:37:12Z","timestamp":1758638232000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA250656"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,22]]},"ISBN":["9781643686110"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia250656","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,22]]}}}