Adding a memory (forgetting) mechanism slightly decreases simulated learning gains overall yet improves alignment with human results, apparently by letting agents discard incorrect rules¶
Claim · All claims
Evidence · 1 study · theoreticalr3·q2·i2medium
Currency · newest study 2023 · not yet checked against its sources · not reviewed by a person · recheck by 2026: tool and model accuracy changes quickly
Subclaims¶
Reading the evidence codes
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the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i2 Introducing the memory mechanism decreased overall learning gains (13.7% vs 22.2%) but did not negate the worked-example benefit for skills, and forgetting agents more effectively utilized correct production rules. → Rachatasumrit 2023
Evidence¶
Rachatasumrit 2023¶
Rachatasumrit, N., Koedinger, K. R., & Carvalho, P. F. (2023). Evidence and theory for why the best example-problem ratio to optimize learning gain depends on knowledge content. https://osf.io/29wpe doi:10.31234/osf.io/eyxfw
q2 · i2 · theoretical · r3
Simulation comparison of AL agents with versus without forgetting (d = 0.7). The authors' interpretation, from a closer examination, is that forgetting agents better discard incorrect production rules and more often select correct ones due to stronger memory activation of later-learned correct rules.
"the introduction of a memory mechanism in simulated learners with forgetting slightly decreases learning gains (22.2% for simulated learners without forgetting vs 13.7% for simulated learners with forgetting), t (948) = 9.409, p < 0.0001, d = 0.7, but does not negate the benefits of worked examples over retrieval practice for skills"
Discussion¶
Related Claims¶
- In simulated learners with forgetting, study-practice yields higher skill gains while practice-only yields higher fact gains, mirroring the human pattern — related
- Ablations show each CogEvolution module contributes: removing ICAP perception, structured retrieval, or evolutionary update degrades mistake precision, learning-curve fit, and alignment — related
- In a human experiment, verbatim facts are learned better from practice-only training while general skills are learned better from example-integrated training (cross-over content-treatment interaction) — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
forgetting-mechanism-decreases-gains-improves-alignment |
title |
Adding a memory (forgetting) mechanism slightly decreases simulated learning gains overall yet improves alignment with human results, apparently by letting agents discard incorrect rules |
description |
Adding a memory (forgetting) mechanism slightly decreases simulated learning gains overall yet improves alignment with human results, apparently by letting agents discard incorrect rules |
status |
review |
evidence_strength |
weak |
newest_evidence |
2023 |
recheck_by |
2026 |
generated |
by process:wiki-ingest on 2026-10-12 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — rachatasumrit-2023 |
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