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Paper Citation Record · LEDGER

A Survey of Reinforcement Learning for Optimization in Automation

As of 8 August 2026, this Paper Citation Record lists 100 of 108 outbound references and 0 inbound Pith citation observations for arXiv:2502.09417.

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

pith.paper-citation-record.v1
2502.09417 v1

Coverage vector

measured 100 of 108 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T21:36:33.708676Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

100 of 108 outbound references displayed

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  • verified fuzzy52
  • unresolved38
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e1228a0a-e975-45b3-960b-cd68601ca37f · outbound

This paper cites an unresolved cited work.

A Survey of Reinforcement Learning for Optimization in Automation Unresolved cited work

Reference 1

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Observation 49bbd95e-d178-4c57-b174-75b2ce8d4323 · outbound

This paper cites Human-level control through deep reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Human-level control through deep reinforcement learning,

Reference 2

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Observation 17c45300-98f1-4106-ab17-45ef09da20fb · outbound

This paper cites Deep reinforcement learning in smart manufacturing: A review and prospects,.

A Survey of Reinforcement Learning for Optimization in Automation Deep reinforcement learning in smart manufacturing: A review and prospects,

Reference 3

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Observation 02c5188b-dbf8-4d96-83f4-55d8b8b03173 · outbound

This paper cites Applications of reinforcement learning in energy systems,.

A Survey of Reinforcement Learning for Optimization in Automation Applications of reinforcement learning in energy systems,

Reference 4

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Observation 1ed9865d-c7da-4b76-89e6-ed0b164afe0d · outbound

This paper cites Reinforcement learning in robotics: A survey,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement learning in robotics: A survey,

Reference 5

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Observation be8b5044-338f-4630-9e31-11e3c918caf5 · outbound

This paper cites Reinforcement learning applied to production planning and control,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement learning applied to production planning and control,

Reference 6

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Observation 4f3c26f1-ea9a-4db5-94b2-03e80f7a6e12 · outbound

This paper cites A review on reinforcement learning: Introduction and applications in industrial process control,.

A Survey of Reinforcement Learning for Optimization in Automation A review on reinforcement learning: Introduction and applications in industrial process control,

Reference 7

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Observation 77ac5118-00f6-4e3a-bb4f-7f65f900aa6f · outbound

This paper cites Deep reinforcement learning for inventory control: A roadmap,.

A Survey of Reinforcement Learning for Optimization in Automation Deep reinforcement learning for inventory control: A roadmap,

Reference 8

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Observation 98f87576-114b-4095-b2d5-197db06aa285 · outbound

This paper cites Metaheuristics in combinatorial optimization: Overview and conceptual comparison,.

A Survey of Reinforcement Learning for Optimization in Automation Metaheuristics in combinatorial optimization: Overview and conceptual comparison,

Reference 9

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Observation 07806f6f-635b-41ba-b86c-0454111b9039 · outbound

This paper cites Deep Reinforcement Learning: An Overview.

A Survey of Reinforcement Learning for Optimization in Automation Deep Reinforcement Learning: An Overview

Reference 10

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Observation c2c0afd4-2d13-4cd1-a148-bdb8649ddbd8 · outbound

This paper cites Deep reinforcement learning: A brief survey,.

A Survey of Reinforcement Learning for Optimization in Automation Deep reinforcement learning: A brief survey,

Reference 11

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Observation 1f4390e4-f241-46f6-bf72-c8dc936162ed · outbound

This paper cites A deep reinforcement learning approach for chemical production scheduling,.

A Survey of Reinforcement Learning for Optimization in Automation A deep reinforcement learning approach for chemical production scheduling,

Reference 12

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Observation 092bbfb2-5b62-4176-9742-e3faa75bcac5 · outbound

This paper cites Intelligent scheduling of discrete automated production line via deep reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Intelligent scheduling of discrete automated production line via deep reinforcement learning,

Reference 13

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Observation 8f581a0b-572f-41da-aa4c-22dbd3f697de · outbound

This paper cites A reinforcement learning method to scheduling problem of steel production process,.

A Survey of Reinforcement Learning for Optimization in Automation A reinforcement learning method to scheduling problem of steel production process,

Reference 14

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Observation e85d2636-7391-4951-88ac-b4fe01ec0ec8 · outbound

This paper cites Distributional Reinforcement Learning for Scheduling of Chemical Production Processes.

A Survey of Reinforcement Learning for Optimization in Automation Distributional Reinforcement Learning for Scheduling of Chemical Production Processes

Reference 15

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Observation 50c6bcaf-e1fa-497e-8c4c-20836238db5d · outbound

This paper cites Reinforcement Learning for Multi-Product Multi-Node Inventory Management in Supply Chains.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement Learning for Multi-Product Multi-Node Inventory Management in Supply Chains

Reference 16

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Observation bd0797c2-3e08-459d-80e3-6980351a603c · outbound

This paper cites Reward shaping to improve the performance of deep reinforcement learning in perishable inventory management,.

A Survey of Reinforcement Learning for Optimization in Automation Reward shaping to improve the performance of deep reinforcement learning in perishable inventory management,

Reference 17

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Observation 1e673c8e-0458-415c-af6f-d97e8da66250 · outbound

This paper cites Cooperative multi-agent reinforcement learning for inventory man- agement,.

A Survey of Reinforcement Learning for Optimization in Automation Cooperative multi-agent reinforcement learning for inventory man- agement,

Reference 18

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Observation 3173f6d7-6862-4fac-bd11-dad2466e3ed0 · outbound

This paper cites MARLIM: Multi-Agent Reinforcement Learning for Inventory Management.

A Survey of Reinforcement Learning for Optimization in Automation MARLIM: Multi-Agent Reinforcement Learning for Inventory Management

Reference 19

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Observation 4ed62436-cd2f-4f9a-a31c-af7d2e58250a · outbound

This paper cites Reinforcement and deep reinforce- ment learning-based solutions for machine maintenance planning, scheduling policies, and optimization,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement and deep reinforce- ment learning-based solutions for machine maintenance planning, scheduling policies, and optimization,

Reference 20

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Observation dc6b4fd7-8851-4360-b2b2-040359d522b5 · outbound

This paper cites Reinforcement learning for dynamic condition-based maintenance of a system with individually repairable components,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement learning for dynamic condition-based maintenance of a system with individually repairable components,

Reference 21

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Observation 75427182-3295-43c2-9978-b96a43c1e503 · outbound

This paper cites Dynamic maintenance model for a repairable multi-component system using deep reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Dynamic maintenance model for a repairable multi-component system using deep reinforcement learning,

Reference 22

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Observation 7d4924d7-3694-44d6-a8f0-1ff7f70a7980 · outbound

This paper cites Aircraft main- tenance check scheduling using reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Aircraft main- tenance check scheduling using reinforcement learning,

Reference 23

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A Survey of Reinforcement Learning for Optimization in Automation Network maintenance planning via multi-agent reinforcement learn- ing,

Reference 24

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Observation 6a0797b0-6f65-465a-9067-0a38339cc954 · outbound

This paper cites Reinforcement learning for statistical process control in manufacturing,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement learning for statistical process control in manufacturing,

Reference 25

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Observation 3faed340-6296-4a10-a72c-96f169277563 · outbound

This paper cites Explainable reinforcement learning in production control of job shop manufacturing system,.

A Survey of Reinforcement Learning for Optimization in Automation Explainable reinforcement learning in production control of job shop manufacturing system,

Reference 26

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Observation 80ed8307-ae0e-4cb1-aae9-2471e4c02f33 · outbound

This paper cites Using process data to generate an optimal control policy via apprenticeship and reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Using process data to generate an optimal control policy via apprenticeship and reinforcement learning,

Reference 27

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Observation 5da87fee-4c7d-4885-9322-685a70ebdbeb · outbound

This paper cites Reinforcement learning for process control with application in semiconductor manufacturing,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement learning for process control with application in semiconductor manufacturing,

Reference 28

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Observation 4d6d80e1-92ca-4cbb-827a-2a2d409815cb · outbound

This paper cites Reinforcement learning for whole-building hvac control and demand response,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement learning for whole-building hvac control and demand response,

Reference 29

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Observation 42893808-7b3d-40aa-803c-21b0fb442131 · outbound

This paper cites Using meta reinforcement learning to bridge the gap between simulation and experiment in energy demand response,.

A Survey of Reinforcement Learning for Optimization in Automation Using meta reinforcement learning to bridge the gap between simulation and experiment in energy demand response,

Reference 30

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Observation 64b59504-e520-4cbb-821e-c4a41865e3b8 · outbound

This paper cites Multiagent reinforce- ment learning for energy management in residential buildings,.

A Survey of Reinforcement Learning for Optimization in Automation Multiagent reinforce- ment learning for energy management in residential buildings,

Reference 31

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Observation a2cfac70-59a5-4229-bec6-c0c34a896022 · outbound

This paper cites Deep reinforcement learning-based demand response for smart facilities energy management,.

A Survey of Reinforcement Learning for Optimization in Automation Deep reinforcement learning-based demand response for smart facilities energy management,

Reference 32

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Observation 1cf0221b-edd3-4756-bef8-a223f754e4ad · outbound

This paper cites Multi-agent deep rein- forcement learning based demand response for discrete manufacturing systems energy management,.

A Survey of Reinforcement Learning for Optimization in Automation Multi-agent deep rein- forcement learning based demand response for discrete manufacturing systems energy management,

Reference 33

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Observation 347e4ab7-b9d9-4049-b8e7-f82367b9c081 · outbound

This paper cites Testbed implementation of reinforcement learning-based demand response energy management system,.

A Survey of Reinforcement Learning for Optimization in Automation Testbed implementation of reinforcement learning-based demand response energy management system,

Reference 34

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Observation 99a2c2d1-40b7-4ffb-8db0-4c5c106cf971 · outbound

This paper cites Deep reinforcement learning for energy management in a microgrid with flexible demand,.

A Survey of Reinforcement Learning for Optimization in Automation Deep reinforcement learning for energy management in a microgrid with flexible demand,

Reference 35

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Observation 7ccde4fa-612d-479f-9c90-c41d7797235d · outbound

This paper cites Energy management for microgrids using a reinforcement learning algorithm,.

A Survey of Reinforcement Learning for Optimization in Automation Energy management for microgrids using a reinforcement learning algorithm,

Reference 36

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 48958e56-0e98-44f3-9545-839af3dfbfaa · outbound

This paper cites Deep reinforcement learning- based energy management strategy for a microgrid with flexible loads,.

A Survey of Reinforcement Learning for Optimization in Automation Deep reinforcement learning- based energy management strategy for a microgrid with flexible loads,

Reference 37

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Observation 6bd8f1a8-8698-4f64-9c64-07cf32505de1 · outbound

This paper cites Energy management in microgrid based on deep rein- forcement learning with expert knowledge,.

A Survey of Reinforcement Learning for Optimization in Automation Energy management in microgrid based on deep rein- forcement learning with expert knowledge,

Reference 38

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.379915Z digest=sha256:9745cb319018803f1c1c59052b143f36218208def66fb1f9941257c187d5b113

Observation 40c6fcb0-efbd-4dc9-9645-8c7c9f416923 · outbound

This paper cites Weather-aware data-driven microgrid energy manage- ment using deep reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Weather-aware data-driven microgrid energy manage- ment using deep reinforcement learning,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:35.026912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.385787Z digest=sha256:c2a27c8f0ba296b0067f743bd7de810b12fa1aae45425bb4e5095f6a7c522979

Observation 11dd84d0-b1e5-44d9-8672-f173fb2df57e · outbound

This paper cites Intelligent multi-microgrid energy management based on deep neural network and model-free reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Intelligent multi-microgrid energy management based on deep neural network and model-free reinforcement learning,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:35.010835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.390987Z digest=sha256:6f0a388938230aa7a6dcb105548e8f0c536c6b0a2bee078a924b4ecddec7657e

Observation f61c2f09-028e-424e-ae15-6307a217de58 · outbound

This paper cites Reinforcement learning in sustainable energy and electric systems: A survey,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement learning in sustainable energy and electric systems: A survey,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.994185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.396006Z digest=sha256:17cef0ca79cded78e8f3d481c3c1e8cf283d7f77a1bf17e74b4f8ea630b8f28c

Observation 1d31bb53-e907-4d2e-8514-a98310da4b04 · outbound

This paper cites Reinforcement learning and its applications in modern power and energy systems: A review,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement learning and its applications in modern power and energy systems: A review,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.976513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.400680Z digest=sha256:92c79b46b0c7cb56a700175fbf53437c7c1c078c6401c5992c160f6a43e0806e

Observation 30c87fc8-0488-4274-ad9f-8a1135833591 · outbound

This paper cites Reinforcement learning for selective key applications in power systems: Recent advances and future challenges,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement learning for selective key applications in power systems: Recent advances and future challenges,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.959177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.406012Z digest=sha256:3a018ab763749f7798f47db38768df342d66e9586ca4e8669822596802fb281a

Observation dff334e1-0be3-4ba1-bf81-5b18b5b9b0af · outbound

This paper cites A systematic study on reinforcement learning based applications,.

A Survey of Reinforcement Learning for Optimization in Automation A systematic study on reinforcement learning based applications,

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T21:36:33.411370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:36:33.411370Z digest=sha256:9c21ccb4c586838b4b67b2f2d077fe8b9686e33413685d104f2818eef771868c

Observation 324fb30e-43f3-468e-a472-472e03a0c28c · outbound

This paper cites End-to-end deep reinforcement learning control for hvac systems in office buildings,.

A Survey of Reinforcement Learning for Optimization in Automation End-to-end deep reinforcement learning control for hvac systems in office buildings,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.932097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.416302Z digest=sha256:7b599526f0105a502af3d27d9a6f598c6aeec5bf97fbc67d2ddd2a7f08a1a272

Observation a9ebe5fc-d33a-4eeb-bd93-074165404b49 · outbound

This paper cites A review of reinforcement learn- ing applications to control of heating, ventilation and air conditioning systems,.

A Survey of Reinforcement Learning for Optimization in Automation A review of reinforcement learn- ing applications to control of heating, ventilation and air conditioning systems,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.918676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.421280Z digest=sha256:b5fbb626464c2cc50391606898eef8c62aba94283cb32f51f39ca413bf91a5b0

Observation e0fcbf14-b415-459d-95fd-f187f1a7eff5 · outbound

This paper cites Safe hvac control via batch reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Safe hvac control via batch reinforcement learning,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.905324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.426203Z digest=sha256:ca34a2a6695ae508b7b16f9a4877fcc5bfab292b8583a8cf0e00d5848dce3940

Observation a6327798-805b-4e04-9d6f-2739c85483b2 · outbound

This paper cites Study on the application of reinforcement learning in the operation optimization of hvac system,.

A Survey of Reinforcement Learning for Optimization in Automation Study on the application of reinforcement learning in the operation optimization of hvac system,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.891041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.431027Z digest=sha256:3eb6e5104fe30b4e2325f2b00a10836e4f521075aa3510bdc23d6eb4a240a9f2

Observation b1da68b9-e07e-446b-8f1a-7cf744b9d80b · outbound

This paper cites Experimental evalu- ation of model-free reinforcement learning algorithms for continuous hvac control,.

A Survey of Reinforcement Learning for Optimization in Automation Experimental evalu- ation of model-free reinforcement learning algorithms for continuous hvac control,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.875809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.436271Z digest=sha256:8297d5eca57d65269b34050557818f5433a0c0a8b80d2ea217f3824a4ff29547

Observation 5698b67f-3bc1-494b-88a5-0200a1c37d8e · outbound

This paper cites Robotic arm motion planning based on curriculum reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Robotic arm motion planning based on curriculum reinforcement learning,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.860984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.441081Z digest=sha256:6dbec520cc4a8e52d8145ddd4a5f157c08bfdf8a39970eea22d099528e5faa08

Observation 70703579-d103-4c26-b4bf-d060840369dc · outbound

This paper cites Reinforcement Learning Based User-Guided Motion Planning for Human-Robot Collaboration.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement Learning Based User-Guided Motion Planning for Human-Robot Collaboration

Reference 51

Resolution
verified exact
local_arxiv, observed 2026-08-07T21:36:34.090096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.445979Z digest=sha256:7f584d98e6adfd07bdf49a69ac18371ac8f89379f7b8bf9a249e01252c5823a7

Observation 8833ca38-04e6-464c-b349-7c238eb01ae6 · outbound

This paper cites Reinforcement learning with prior policy guidance for motion planning of dual-arm free-floating space robot,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement learning with prior policy guidance for motion planning of dual-arm free-floating space robot,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.846502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.451666Z digest=sha256:68610c211fc4686b80193f58bff34733bb7187b4d523ca2453fd1aa84b8a292f

Observation 7dc13f4f-04f4-4dd0-abad-6f1e55ef17bc · outbound

This paper cites Dext-Gen: Dexterous Grasping in Sparse Reward Environments with Full Orientation Control.

A Survey of Reinforcement Learning for Optimization in Automation Dext-Gen: Dexterous Grasping in Sparse Reward Environments with Full Orientation Control

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-08-07T21:36:34.065513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.456710Z digest=sha256:84ab8f91b18c1d77a4da59dd468f917ea26f1b89277c8e0f9bd16bca8be9748b

Observation 6618b32d-3e96-4ce5-a2f6-11defec4054b · outbound

This paper cites Robotic grasping using deep reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Robotic grasping using deep reinforcement learning,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.831637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.461980Z digest=sha256:420a9abc9713c96034552612107027a2bfe8d6d1f175864f0191813d4da2e235

Observation 9fbf6898-67ec-4459-8a8b-a17efeaa3f37 · outbound

This paper cites Mrcdrl: Multi-robot coordination with deep reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Mrcdrl: Multi-robot coordination with deep reinforcement learning,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.817018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.467164Z digest=sha256:7c0fc56c911317ef8eb784c0436b0c79b3383a12f2372d8e08df533d8a9b56da

Observation 304cb149-2520-4a71-b5f9-6dda9c93cd03 · outbound

This paper cites Towards pick and place multi robot coordination using multi-agent deep reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Towards pick and place multi robot coordination using multi-agent deep reinforcement learning,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.801866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.472557Z digest=sha256:b13d038103aca34a69af618fcd6039c906b820884cc181192b86234723dd8fe0

Observation e26e0375-1e66-4b32-93e4-defe3ed8697e · outbound

This paper cites Human-centered collaborative robots with deep reinforcement learn- ing,.

A Survey of Reinforcement Learning for Optimization in Automation Human-centered collaborative robots with deep reinforcement learn- ing,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.786998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.477393Z digest=sha256:ae6fa13969099a2efbe7a86346deaf95fdb380f2cea6314f3741670cac27070a

Observation a5329fba-cc14-4147-9432-8827cc9de23a · outbound

This paper cites Explainable reinforcement learning for human-robot collaboration,.

A Survey of Reinforcement Learning for Optimization in Automation Explainable reinforcement learning for human-robot collaboration,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.771673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.482259Z digest=sha256:9f21e3e2d1761cd3ca94744eeacc1e8509df57b97a83c15476d95017fef214bc

Observation e9c26b50-51b6-46d4-a109-54ad10613235 · outbound

This paper cites Real-world human-robot collaborative reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Real-world human-robot collaborative reinforcement learning,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.755910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.487077Z digest=sha256:4b47bfca09ee62414e12d962dded08ca2aea48330707824d774ecb38115f2734

Observation a3cebd9a-7306-41e0-980e-e3be2a21d1e0 · outbound

This paper cites Human-Robot Gym: Benchmarking Reinforcement Learning in Human-Robot Collaboration.

A Survey of Reinforcement Learning for Optimization in Automation Human-Robot Gym: Benchmarking Reinforcement Learning in Human-Robot Collaboration

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-08-07T21:36:34.043976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.492184Z digest=sha256:59db74231433c11934cfb421f211099756507332ad248d64a998cdb908e1e38c

Observation 1d975f13-1b8d-4322-bc7c-b8b386f7c0f1 · outbound

This paper cites Towards safe human-robot collaboration using deep reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Towards safe human-robot collaboration using deep reinforcement learning,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.741221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.497527Z digest=sha256:a610c32491a810269e8bee482ac957022f9509b4e4eb47ffe22029d3e716a410

Observation 4d24db4b-5d3e-4ce4-808a-72c701bc2497 · outbound

This paper cites A framework and algorithm for human-robot collaboration based on multimodal reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation A framework and algorithm for human-robot collaboration based on multimodal reinforcement learning,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.726034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.502565Z digest=sha256:f1f2cdf6dddf1e73fa00fef16fe43145d28a5c3fb0ea7abee82a05fbee978d26

Observation 07085747-d61d-4340-a188-6e10b03d593c · outbound

This paper cites A survey of learning-based robot motion planning,.

A Survey of Reinforcement Learning for Optimization in Automation A survey of learning-based robot motion planning,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.711109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.507880Z digest=sha256:d6179a89617c2935e3228f42bf7b6e03c1ef31377627f454a56f3669eb7aa649

Observation b5f86b26-6acf-48ce-aa1f-5f4094a570ea · outbound

This paper cites A survey on deep reinforcement learning algorithms for robotic manipulation,.

A Survey of Reinforcement Learning for Optimization in Automation A survey on deep reinforcement learning algorithms for robotic manipulation,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.696771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.512848Z digest=sha256:6abe6b7d7611d9b23bada83a1bc3d122206a715c7b069fddedff1b5bb5d64d95

Observation a6ade5fc-00bc-479d-a77f-8bf827705595 · outbound

This paper cites Reward shaping to learn natural object manipulation with an anthropomorphic robotic hand and hand pose priors via on- policy reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Reward shaping to learn natural object manipulation with an anthropomorphic robotic hand and hand pose priors via on- policy reinforcement learning,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.682569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.517671Z digest=sha256:30e24210ac5096a786ac618501e25a7d36a1052eb10d01c368bd4a9ab47729c8

Observation 544cbe48-d6e9-47b8-8218-3278f40e9633 · outbound

This paper cites Enhancing robotic grasping of free-floating targets with soft actor-critic algorithm and tactile sensors: a focus on the pre-grasp stage,.

A Survey of Reinforcement Learning for Optimization in Automation Enhancing robotic grasping of free-floating targets with soft actor-critic algorithm and tactile sensors: a focus on the pre-grasp stage,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.667452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.522486Z digest=sha256:769973ce4cc2d49de006c8d68b206d678ee24977f3d66f99841f614a3fa90419

Observation 4e1ef3d1-d871-46c9-9656-25a006853d42 · outbound

This paper cites Reinforcement learning for multi-robot system: A review,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement learning for multi-robot system: A review,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.651171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.528484Z digest=sha256:66018e5ac0b52d549f81570aa302b8eba68288f6dcc8a5961f747fd3e1328a68

Observation ce4dd452-ff06-4335-8d09-119c9fbe2f4e · outbound

This paper cites Coordination of a multi robot system for pick and place using reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Coordination of a multi robot system for pick and place using reinforcement learning,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.633058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.534696Z digest=sha256:53141065c0adc60d41303388b4dc3d979df707383c4d56cb5483733b31744a7b

Observation 501b8719-94cd-4d3c-bf9b-104c37ee22c8 · outbound

This paper cites an unresolved cited work.

A Survey of Reinforcement Learning for Optimization in Automation Unresolved cited work

Reference 69

Resolution
unresolved
raw_fallback, observed 2026-08-07T21:36:34.617407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.540512Z digest=sha256:2b70f2fdc0bec7dec2db4005dfc8af5f2f5df4d8f6f215d9b6ab3c5acda9e1a9

Observation 16a6ebd3-002d-4a7a-ad9d-7b483a9f128d · outbound

This paper cites Adaptive coordination of multiple learning strategies in brains and robots,.

A Survey of Reinforcement Learning for Optimization in Automation Adaptive coordination of multiple learning strategies in brains and robots,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.601441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.546869Z digest=sha256:97a9cfc32ef117986d4dc4f8078691afa41f45f4721c52e3f9cae5a5722440d2

Observation 550ce57c-396e-4014-87b6-9c82f2c81f7d · outbound

This paper cites Study of sample efficiency improvements for reinforcement learning algorithms,.

A Survey of Reinforcement Learning for Optimization in Automation Study of sample efficiency improvements for reinforcement learning algorithms,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.585485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.552190Z digest=sha256:b7c300367e37d7aadefe0aca596ac3564cb32651b761a052100c3c57248efee0

Observation 9fdb04d5-b5d0-4e98-b5ec-1b0ff458c82b · outbound

This paper cites Measuring Progress in Deep Reinforcement Learning Sample Efficiency.

A Survey of Reinforcement Learning for Optimization in Automation Measuring Progress in Deep Reinforcement Learning Sample Efficiency

Reference 72

Resolution
verified exact
local_arxiv, observed 2026-08-07T21:36:34.022989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.558901Z digest=sha256:a3aa47d3974eeb627efba026b7d493cef66f365de551b74ae72c9b34ea58dc3c

Observation d842fd78-6b4b-4bf4-9c6a-6f5c545a560e · outbound

This paper cites Maximum Mutation Reinforcement Learning for Scalable Control.

A Survey of Reinforcement Learning for Optimization in Automation Maximum Mutation Reinforcement Learning for Scalable Control

Reference 73

Resolution
verified exact
local_arxiv, observed 2026-08-07T21:36:34.001403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.565054Z digest=sha256:c583ffed4389d2a77f16bf5c268273f0f38c5ac9adf2fa6ffb8d36dd162bd4d9

Observation b3b6ec98-e4c1-4072-a26f-c0d1023d67c7 · outbound

This paper cites Sample efficient reinforcement learning method via high efficient episodic memory,.

A Survey of Reinforcement Learning for Optimization in Automation Sample efficient reinforcement learning method via high efficient episodic memory,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.569138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 1b547937-483b-4429-9ad4-4913ae6e7ab8 · outbound

This paper cites Efficient online reinforcement learning with offline data,.

A Survey of Reinforcement Learning for Optimization in Automation Efficient online reinforcement learning with offline data,

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-07T21:36:33.576696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:36:33.576696Z digest=sha256:5fa00eebef9094ec4595f081d5c958e3391fc56271e264040085e73e12a55480

Observation 5bc23ff2-040c-4f99-929c-b7fbd140bfed · outbound

This paper cites Breaking the sample size barrier in model-based reinforcement learning with a generative model,.

A Survey of Reinforcement Learning for Optimization in Automation Breaking the sample size barrier in model-based reinforcement learning with a generative model,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.539665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.582695Z digest=sha256:485257afcf6fb7534d6ee65dbed2ecb6b3384d01bd67ee9569eb7b68bc5461d3

Observation 97b57b1d-a763-40ee-ad38-fa8bdd7c3e30 · outbound

This paper cites Elastic step ddpg: Multi-step reinforcement learning for improved sample efficiency,.

A Survey of Reinforcement Learning for Optimization in Automation Elastic step ddpg: Multi-step reinforcement learning for improved sample efficiency,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.522087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.587857Z digest=sha256:7b20518ec6ba1e6db245a863866d9d8de26995abf47026ae42a882d07d8c700f

Observation ee8173eb-355a-4df7-848d-84d4bd778d6b · outbound

This paper cites Sample-efficient reinforcement learning via conservative model-based actor-critic,.

A Survey of Reinforcement Learning for Optimization in Automation Sample-efficient reinforcement learning via conservative model-based actor-critic,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.505362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.593984Z digest=sha256:5884e7a0719087cfc0b8d60c5c16c50dcddfda6ea813044c037dc4cbc5a219e7

Observation 0ddf61cb-00a0-4b3c-8ec3-9aebb00f6f46 · outbound

This paper cites Safety robustness of reinforcement learning policies: A view from robust control,.

A Survey of Reinforcement Learning for Optimization in Automation Safety robustness of reinforcement learning policies: A view from robust control,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.490108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.599188Z digest=sha256:2fba2021932a8176508cf1b1c97b8aaa08417d3c48920271fa400d54254d78d2

Observation 2cc06383-7502-4214-af5e-5a22cf820ace · outbound

This paper cites Safe Reinforcement Learning with Dual Robustness.

A Survey of Reinforcement Learning for Optimization in Automation Safe Reinforcement Learning with Dual Robustness

Reference 80

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verified exact
local_arxiv, observed 2026-08-07T21:36:33.979594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.604825Z digest=sha256:32e4d7c4e3eecb6a079a46da67d53aa7a31649ce2f37fac97727619046acba5e

Observation d9c98fea-5183-47eb-b67d-026444cd6663 · outbound

This paper cites On the Robustness of Safe Reinforcement Learning under Observational Perturbations.

A Survey of Reinforcement Learning for Optimization in Automation On the Robustness of Safe Reinforcement Learning under Observational Perturbations

Reference 81

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unresolved
no resolver link, observed 2026-08-07T21:36:33.610142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:36:33.610142Z digest=sha256:270233add4670647c7fc702bacd7976a64d7a3830a8c742957ab5598b2fe5360

Observation 5457f1a7-3bd7-47a5-bc78-5d901f1baab8 · outbound

This paper cites Safe reinforcement learning using robust control barrier functions,.

A Survey of Reinforcement Learning for Optimization in Automation Safe reinforcement learning using robust control barrier functions,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.475887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.616906Z digest=sha256:314e667c09a422c6aaaadfad4c1352ab5751f6244c442bd501c076908ae2eaed

Observation 9c128383-c9dc-4c0d-8e04-0710731d6ad2 · outbound

This paper cites Safe reinforcement learning using robust action governor,.

A Survey of Reinforcement Learning for Optimization in Automation Safe reinforcement learning using robust action governor,

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.461578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.621836Z digest=sha256:47883c915686c80da0cdec647610a1cc6b21d491e3ecaaf964fe5dad54be9931

Observation 226086d9-4c0c-49b2-9579-c358e5e98367 · outbound

This paper cites Safe reinforcement learning using robust mpc,.

A Survey of Reinforcement Learning for Optimization in Automation Safe reinforcement learning using robust mpc,

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-07T21:36:33.626931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:36:33.626931Z digest=sha256:20d931d7e3b30b98e37de39f5ad37f7ba9e5dac4d0a5f8d75fb298ab51ff29a6

Observation 0d91ed9e-980d-42b9-8eca-41f78d83e390 · outbound

This paper cites Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees.

A Survey of Reinforcement Learning for Optimization in Automation Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees

Reference 85

Resolution
verified exact
local_arxiv, observed 2026-08-07T21:36:33.939102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.631729Z digest=sha256:e6239f8388fac7e06388bffae8a9e7385466170d2856b6c38fcd1e9ea7f4a6ad

Observation dff55c0a-093b-4d0a-90fe-d9344f031119 · outbound

This paper cites Task-agnostic safety for rein- forcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Task-agnostic safety for rein- forcement learning,

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.438028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.637192Z digest=sha256:52233cc9d7fcbd58c74298b8f3e5ed5220a48487772b0f4e0cf82d47ea478875

Observation 29b3ce88-d0b3-4d8a-9a68-69d81ff0f06d · outbound

This paper cites Falsification-based robust ad- versarial reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Falsification-based robust ad- versarial reinforcement learning,

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.423999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.641895Z digest=sha256:e05c741612e66c2393db001350a30cdf94c3aa6879ab2aa194d3496386755cfd

Observation 503dd278-7361-4b56-8667-d90b26627b8f · outbound

This paper cites A Survey on Interpretable Reinforcement Learning.

A Survey of Reinforcement Learning for Optimization in Automation A Survey on Interpretable Reinforcement Learning

Reference 88

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unresolved
no resolver link, observed 2026-08-07T21:36:33.646549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:36:33.646549Z digest=sha256:1e734cd10f52ddf4145349303de8c89446e25ecee1912ce6a101718cc79fb95e

Observation 36328faf-762e-4051-a9a9-6e03687c19f5 · outbound

This paper cites Interpretable Model-based Hierarchical Reinforcement Learning using Inductive Logic Programming.

A Survey of Reinforcement Learning for Optimization in Automation Interpretable Model-based Hierarchical Reinforcement Learning using Inductive Logic Programming

Reference 89

Resolution
verified exact
local_arxiv, observed 2026-08-07T21:36:33.900439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.651576Z digest=sha256:c60b35c5f07173ee0cbd2d2d32a357907fd6f16328072487511ab87b19e3a932

Observation 039c8826-59dd-45a1-86d0-63e374e46491 · outbound

This paper cites There is no Accuracy-Interpretability Tradeoff in Reinforcement Learning for Mazes.

A Survey of Reinforcement Learning for Optimization in Automation There is no Accuracy-Interpretability Tradeoff in Reinforcement Learning for Mazes

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-07T21:36:33.656651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:36:33.656651Z digest=sha256:6a27037bece654dd8015902e266f3958a62d798568334778a5e2e76d53b48fab

Observation 060a3d21-8994-4ba3-9c77-72db014205a7 · outbound

This paper cites What do rein- forcement learning models measure? interpreting model parameters in cognition and neuroscience,.

A Survey of Reinforcement Learning for Optimization in Automation What do rein- forcement learning models measure? interpreting model parameters in cognition and neuroscience,

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.407812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.661666Z digest=sha256:1bd51254e83520066b5421bfc34041bc3fc13bf453a1dae7f82501fca6bd30cd

Observation 3f9ff627-597a-4669-a12c-dd8d83ed650e · outbound

This paper cites Reinforcement learning interpretation methods: A survey,.

A Survey of Reinforcement Learning for Optimization in Automation Reinforcement learning interpretation methods: A survey,

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.390612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.666689Z digest=sha256:c4c62c1f644e0eab9c1ba91f33f79945f67ff2fbc67f0f2987eedbe1b9cdd294

Observation b4292e42-6ae8-4514-a3d1-19e206c1950a · outbound

This paper cites Self- supervised discovering of interpretable features for reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Self- supervised discovering of interpretable features for reinforcement learning,

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.374926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.671778Z digest=sha256:bb2dc65aa77c38fdf5436e24ab564b93ffb5db90c3ed73b0606c594370009ffd

Observation 9f8389df-804e-4f18-8799-c8c09b7af67c · outbound

This paper cites Learning sparse evidence-driven interpretation to understand deep reinforcement learning agents,.

A Survey of Reinforcement Learning for Optimization in Automation Learning sparse evidence-driven interpretation to understand deep reinforcement learning agents,

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.358993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.676726Z digest=sha256:1772d83542da9281c13c071c607de2c75d1e8656ca5bac3d409c14e5b8a24c8c

Observation cc37d66b-bf1a-460c-824d-7a63bbd33147 · outbound

This paper cites Meta- learning in neural networks: A survey,.

A Survey of Reinforcement Learning for Optimization in Automation Meta- learning in neural networks: A survey,

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.342061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.681931Z digest=sha256:56e1c904bda5a2cbdbea6e3049f3bc79c1702f4e5f001d5808189d6bc701717f

Observation a5e3b93f-c857-4a58-bed6-1a4378ac9865 · outbound

This paper cites Learning action translator for meta reinforcement learning on sparse-reward tasks,.

A Survey of Reinforcement Learning for Optimization in Automation Learning action translator for meta reinforcement learning on sparse-reward tasks,

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.325714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.687168Z digest=sha256:6c84ae77564eaa1be9a74c5e47dc23f9934c37c79461c43f16be626fafcf9250

Observation 126117cc-c59f-4078-8cbd-3923a748c2a5 · outbound

This paper cites Curriculum learning for reinforcement learning domains: A framework and survey,.

A Survey of Reinforcement Learning for Optimization in Automation Curriculum learning for reinforcement learning domains: A framework and survey,

Reference 97

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unresolved
no resolver link, observed 2026-08-07T21:36:33.692403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:36:33.692403Z digest=sha256:810f334cc13ac05ba5a556aa2944d38f5f50474e8a36dacff4cd3812faa745ec

Observation 808b3c83-1777-459a-a754-3ada3a3aa015 · outbound

This paper cites Effective reinforcement learning using transfer learning,.

A Survey of Reinforcement Learning for Optimization in Automation Effective reinforcement learning using transfer learning,

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.299553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.697555Z digest=sha256:aa5273b4cbf6f06edc563e1a60824bf7f1270a605c4a17b26573aaa78f330f93

Observation 1268171f-12d1-4267-902c-662832d31dfe · outbound

This paper cites Multi-source transfer learning for deep model-based reinforcement learning,.

A Survey of Reinforcement Learning for Optimization in Automation Multi-source transfer learning for deep model-based reinforcement learning,

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.284441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T21:36:33.702827Z digest=sha256:f0c741e99a5c938dbdc42fb9200f886d2e6bcb658f9103eb24fa3a599aeccbd7

Observation 1f0bd06a-6bff-4527-8419-76ff699b49a9 · outbound

This paper cites Efficient meta reinforcement learning for preference-based fast adaptation,.

A Survey of Reinforcement Learning for Optimization in Automation Efficient meta reinforcement learning for preference-based fast adaptation,

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T21:36:34.266401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Pith citing papers

No inbound Pith citation observations are available.