pith:FW7ADB3R
Ask Only When Needed: Proactive Retrieval from Memory and Skills for Experience-Driven Lifelong Agents
Lifelong agents learn an explicit policy for retrieving past experience only when it improves the next decision.
arxiv:2604.20572 v2 · 2026-04-22 · cs.CL
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\usepackage{pith}
\pithnumber{FW7ADB3RSNC6OPWWYJAQIEKTJF}
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Claims
Experiments on SciWorld, AlfWorld, and StuLife show that ProactAgent consistently improves lifelong agent performance, achieving success rates of 73.50% on SciWorld and 71.28% on AlfWorld while substantially reducing retrieval overhead, and attains performance competitive with proprietary models on StuLife.
That comparing continuations from identical interaction prefixes with and without retrieval supplies unbiased, step-level supervision for the retrieval policy without introducing selection bias or reward hacking.
ProactAgent learns a proactive retrieval policy via reinforcement learning on paired task continuations, improving lifelong agent performance and cutting retrieval overhead on SciWorld, AlfWorld, and StuLife.
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Receipt and verification
| First computed | 2026-06-05T01:14:39.277588Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
2dbe0187719345e73ed6c241041153494a4002ef49e91e88b192ec24a8d0e021
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/FW7ADB3RSNC6OPWWYJAQIEKTJF \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 2dbe0187719345e73ed6c241041153494a4002ef49e91e88b192ec24a8d0e021
Canonical record JSON
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