Metraipolis › archive › dc_fe07fb2ac686

Probing Stability-Plasticity Tradeoffs in Agent Memory through Cognitive Experimental Paradigms — arXiv:2609.30558

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.30558
License (as archived): CC0-1.0
Archived: 2026-10-08T01:39:19.967Z
SHA-256 of the archived text: 8db4e3fd1ba0e792317978131400fa3b590b907778894f99c54dacd13793bfb3
Stable URL of this page: https://metraipolis.com/documento/dc_fe07fb2ac686

How to cite

Probing Stability-Plasticity Tradeoffs in Agent Memory through Cognitive Experimental Paradigms — arXiv:2609.30558 — arXiv (en), https://arxiv.org/abs/2609.30558 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_fe07fb2ac686 (Metraipolis archive dc_fe07fb2ac686, sha256 8db4e3fd1ba0e792317978131400fa3b590b907778894f99c54dacd13793bfb3)

BibTeX

@misc{dcfe07fb2ac686,
  title = {Probing Stability-Plasticity Tradeoffs in Agent Memory through Cognitive Experimental Paradigms — arXiv:2609.30558},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.30558},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_fe07fb2ac686; sha256 8db4e3fd1ba0e792317978131400fa3b590b907778894f99c54dacd13793bfb3},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.30558. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Agent memory systems are increasingly used to maintain long-term user preferences, task states and evolving facts, but current evaluations often collapse memory behavior into final-answer accuracy. We introduce MemProbe, a cognitive-science-inspired framework for diagnosing stability-plasticity tradeoffs in agent memory. The framework is motivated by a core insight from cognitive memory research: memory is reconstructive and shaped by interference, source reliability, reinforcement, and reactivation. MemProbe turns this insight into four reusable experimental paradigms (interference, misinformation, consolidation strength, and reconsolidation window) that manipulate when a memory should be updated, preserved, or treated as uncertain. It further decomposes correctness into behavioral profiles that reveal how systems update, preserve, attribute, and temporally organize information. We instantiate these paradigms in a 56-episode diagnostic suite and evaluate six incremental memory systems under a unified protocol. Results show that systems with similar aggregate scores exhibit distinct behavioral profiles. MemProbe provides such a diagnostic lens, turning aggregate performance into interpretable profiles of memory maintenance over time. Code is available at this https URL .

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-09-28 in cs.AI).
Categorie arXiv: Computation and Language (cs.CL) ; Artificial Intelligence (cs.AI); Machine Learning (cs.LG).
Pagina del lavoro: https://arxiv.org/abs/2609.30558 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-08T01:12:14.450Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-09-28?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).