{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T16:59:08Z","timestamp":1782233948263,"version":"3.54.5"},"reference-count":0,"publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AAAI-SS"],"abstract":"<jats:p>Efficient sorting of critical waste materials (e.g., rare-earth elements, specific plastics, nuclear components) is essential for resource recovery and environmental safety. Deep learning models excel in visual-based sorting but fail to adapt to evolving waste streams without catastrophic forgetting of previously learned knowledge. This paper presents a continual learning framework for robotic waste sorting using classical experience replay. Our approach maintains a balanced memory buffer with reservoir sampling, enabling sequential learning of new material categories while preserving accuracy on previously encountered ones. Experiments on a curated dataset of critical waste materials demonstrate that our method reduces average forgetting compared to fine-tuning baselines and maintains sorting accuracy above 29% on old tasks while integrating new classes with minimal additional data. This work provides a pathway toward adaptive and sustainable waste management systems capable of lifelong operation in dynamic industrial environments.<\/jats:p>","DOI":"10.1609\/aaaiss.v9i1.42908","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T16:33:45Z","timestamp":1782232425000},"page":"77-82","source":"Crossref","is-referenced-by-count":0,"title":["Mitigating Catastrophic Forgetting in Robotic Waste Sorting: A Continual Learning Framework with Dynamic Experience Replay"],"prefix":"10.1609","volume":"9","author":[{"given":"Vlad","family":"Licaret","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youcef","family":"Djenouri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arnoud","family":"Jochemsen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmed Nabil","family":"Belbachir","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"9382","published-online":{"date-parts":[[2026,6,23]]},"container-title":["Proceedings of the AAAI Symposium Series"],"original-title":[],"link":[{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI-SS\/article\/download\/42908\/50468","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI-SS\/article\/download\/42908\/50468","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T16:33:45Z","timestamp":1782232425000},"score":1,"resource":{"primary":{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI-SS\/article\/view\/42908"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,23]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,6,23]]}},"URL":"https:\/\/doi.org\/10.1609\/aaaiss.v9i1.42908","relation":{},"ISSN":["2994-4317"],"issn-type":[{"value":"2994-4317","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,23]]}}}