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Paper Citation Record · LEDGER

Evolutionary Policy Optimization

As of 17 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2504.12568.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2504.12568 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:32:58.885798Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

25 of 25 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved22
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b43e0d69-3662-49fe-a12a-070e4320112f · outbound

This paper cites Optuna: A Next-generation Hyperparameter Optimization Framework.

Evolutionary Policy Optimization Optuna: A Next-generation Hyperparameter Optimization Framework

Reference 1

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unresolved
no resolver link, observed 2026-08-16T12:32:58.756420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.756420Z digest=sha256:2767d28f7d4b382839526bd29d0a4778f948f1f8cdca85214349adf851c82b10

Observation d20f1554-c2e8-409b-abf5-044423659c62 · outbound

This paper cites The Arcade Learning Environment: An Evaluation Platform for General Agents.

Evolutionary Policy Optimization The Arcade Learning Environment: An Evaluation Platform for General Agents

Reference 2

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unresolved
no resolver link, observed 2026-08-16T12:32:58.762671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.762671Z digest=sha256:a96143026586733e0951072e0abf5e12a88f90fd9f34c526e2cae0d34699fd50

Observation c1c60fa0-26be-4f0a-bc71-5487c7564c4c · outbound

This paper cites an unresolved cited work.

Evolutionary Policy Optimization Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-16T12:32:59.395194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T12:32:58.767779Z digest=sha256:5ea5fbf294303a3aa16634dd171975a403e307e0f3a48d798019057ccd4b8c14

Observation 1ea9a75e-2d0e-4a74-887f-317202e05aaa · outbound

This paper cites Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents.

Evolutionary Policy Optimization Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents

Reference 4

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no resolver link, observed 2026-08-16T12:32:58.773221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.773221Z digest=sha256:71160870a95675110d13cbf0748ea83da2b112388c042cc1156552e235d1bda2

Observation 2cb7c1eb-051b-49b7-a2f5-143b300fc372 · outbound

This paper cites Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription.

Evolutionary Policy Optimization Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-08-16T12:32:59.141680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T12:32:58.778414Z digest=sha256:316c9fa678dd21d996267beacf9395daf7c471d761cfc1db0067b111ad6259c1

Observation 7c9a5b4c-a97a-408c-b787-f362a8679664 · outbound

This paper cites Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor.

Evolutionary Policy Optimization Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Reference 6

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unresolved
no resolver link, observed 2026-08-16T12:32:58.784184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.784184Z digest=sha256:c9df270d9b900e8da0e0bfe58f6d3a73d3be2ab5feabd7590134cd2958f2157b

Observation fc0cccf9-6d52-4c91-965a-83d179ab36c2 · outbound

This paper cites LeCun, B.

Evolutionary Policy Optimization LeCun, B

Reference 7

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unresolved
no resolver link, observed 2026-08-16T12:32:58.790142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.790142Z digest=sha256:2c5a1be4e1583e7ace1afe470aadf0333147ea1f12105252d433907e5e651b82

Observation 7834643c-c9e7-45ae-96f0-c036a218c2f8 · outbound

This paper cites an unresolved cited work.

Evolutionary Policy Optimization Unresolved cited work

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-16T12:32:58.795130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.795130Z digest=sha256:8f4ae6dc3069b3e899f97c6d78cc6ae59bf2d7a031cec3bab2e7593711d29554

Observation 258092c3-9f51-4d33-97ca-a7403929e0c3 · outbound

This paper cites Evolving Deep Neural Networks.

Evolutionary Policy Optimization Evolving Deep Neural Networks

Reference 9

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no resolver link, observed 2026-08-16T12:32:58.801681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.801681Z digest=sha256:e2bb6fa31f30eaa6d2ee6b8415a25871bd520fe369107b7c60085f890ae2a9c3

Observation 6fcf6ed2-cde1-4d81-866b-802490fe6666 · outbound

This paper cites Asynchronous Methods for Deep Reinforcement Learning.

Evolutionary Policy Optimization Asynchronous Methods for Deep Reinforcement Learning

Reference 10

Resolution
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no resolver link, observed 2026-08-16T12:32:58.807134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.807134Z digest=sha256:51eddef350aad5c25ca3e1e410f6b29398dd7e7546796739456b11a01f61dd8f

Observation 64e880e7-d454-43be-ad6d-18209562856c · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Evolutionary Policy Optimization Playing Atari with Deep Reinforcement Learning

Reference 11

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no resolver link, observed 2026-08-16T12:32:58.812868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.812868Z digest=sha256:47836d68053026c36eab9af8ec903105bf33d1f62ea07ade62c344431cd9634c

Observation b666516e-87ca-44fc-85df-08d78dbcdfdb · outbound

This paper cites Rusu, Joel Veness, Marc G.

Evolutionary Policy Optimization Rusu, Joel Veness, Marc G

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-16T12:32:58.818950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.818950Z digest=sha256:efcf0e62a3e478377b2d0094229638e7043535b0c8ae420b2a4cc4847909f006

Observation f0050898-77fa-435c-b008-9fb808fcd08a · outbound

This paper cites an unresolved cited work.

Evolutionary Policy Optimization Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-16T12:32:59.287611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-16T12:32:58.829865Z digest=sha256:1dc90e282c87a96b51c34ec88fe4c5f27e3154b06150ce624d6344ce877b2510

Observation 3a5fd67d-ea90-4b98-9529-2217ce5903cc · outbound

This paper cites an unresolved cited work.

Evolutionary Policy Optimization Unresolved cited work

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-16T12:32:58.834697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.834697Z digest=sha256:0010091601789ab9f48f0d8fcd1e6ab942661011f80a14fda88b35d79d530db5

Observation 25d2c83d-e0f4-486c-942a-89c1e86cb5ad · outbound

This paper cites an unresolved cited work.

Evolutionary Policy Optimization Unresolved cited work

Reference 15

Resolution
malformed identifier
no resolver link, observed 2026-08-16T12:32:58.839428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.839428Z digest=sha256:94db3ae425064610e6226fbbdb1c3e38769e2b2994390426aec7237ad60c6180

Observation ba8af3ac-e005-46d7-b247-1ca2274ffc58 · outbound

This paper cites Evolution Strategies as a Scalable Alternative to Reinforcement Learning.

Evolutionary Policy Optimization Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-16T12:32:58.845268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.845268Z digest=sha256:cad666221f56d13af33f406921f47bd2886ceb70e06badc1548db67f6e22a920

Observation 5f0588a6-41f2-43c1-a5ce-a6bb4de0b74f · outbound

This paper cites Trust Region Policy Optimization.

Evolutionary Policy Optimization Trust Region Policy Optimization

Reference 17

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unresolved
no resolver link, observed 2026-08-16T12:32:58.851369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.851369Z digest=sha256:d3c18bc94bd59409ef93a650e8f1145a7d7bd7a6ff183bfea8c883481c48a000

Observation f0d862f1-4a49-4d51-a95d-0cda71fdf471 · outbound

This paper cites an unresolved cited work.

Evolutionary Policy Optimization Unresolved cited work

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-16T12:32:58.856040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.856040Z digest=sha256:0dfe75bdf234ee00d4c1c9bc8b55a9d7e71fbcbd40ad0309d166a2ed24ed5f66

Observation 29aeddba-1058-45d2-8312-57c3cb8caf97 · outbound

This paper cites Optimal Advertising for Information Products.

Evolutionary Policy Optimization Optimal Advertising for Information Products

Reference 19

Resolution
malformed identifier
no resolver link, observed 2026-08-16T12:32:58.865853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.865853Z digest=sha256:274040a661cb2334b1ae279dcf6efb7fcd5eeef620fb0c62b69da3b3cdc99f2d

Observation b4345154-42eb-4fa7-abc7-a9518981930b · outbound

This paper cites Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning.

Evolutionary Policy Optimization Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

Reference 20

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unresolved
no resolver link, observed 2026-08-16T12:32:58.871043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.871043Z digest=sha256:f4b6d4a7676058ba1242af8040550e36da7a8d850a6c87f019d09f269191f63a

Observation 8f7cf51d-543c-47a8-b916-37a21ed4ca51 · outbound

This paper cites an unresolved cited work.

Evolutionary Policy Optimization Unresolved cited work

Reference 21

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unresolved
no resolver link, observed 2026-08-16T12:32:58.876318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.876318Z digest=sha256:708818bb899cce94320256d4e3678c0dfbba1f48d0f4aeb1a8ff4b02534e5c61

Observation b59266da-ddab-4f2d-ae8a-9ef361fb60b1 · outbound

This paper cites Sample Efficient Actor-Critic with Experience Replay.

Evolutionary Policy Optimization Sample Efficient Actor-Critic with Experience Replay

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-16T12:32:58.880894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.880894Z digest=sha256:f65ecb14963d75aa3117a0e03c43a917e7fdf2db934921567dcff515e5cc17d9

Observation f17263cc-c28f-4303-8056-6af0d767a132 · outbound

This paper cites Williams.

Evolutionary Policy Optimization Williams

Reference 23

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unresolved
no resolver link, observed 2026-08-16T12:32:58.885798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.885798Z digest=sha256:92c57af0e78bfa3cbb540869d763e6a89e00cb915f64f3e9e0774f58d0999b52

Observation af23db3d-fdc9-40ad-aacb-e6d5f6d35e2f · outbound

This paper cites Nature 518 (2015), 529–533.

Evolutionary Policy Optimization Nature 518 (2015), 529–533

Reference 2015

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unresolved
no resolver link, observed 2026-08-16T12:32:58.824420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.824420Z digest=sha256:200efd9eea6d951faa88d284edc0db5ba8715775c1e749c97c5a5edb917b79f3

Observation 39309e09-c37e-414e-b44c-d727f10cf18c · outbound

This paper cites Proximal Policy Optimization Algorithms.

Evolutionary Policy Optimization Proximal Policy Optimization Algorithms

Reference 2017

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no resolver link, observed 2026-08-16T12:32:58.861073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:32:58.861073Z digest=sha256:313994d49e6d8a67f60788835195a22a1dc230f0edee469e175a90382f4f57db

Pith citing papers

No inbound Pith citation observations are available.