Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T23:23:38.957539Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2511.06229.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T23:23:38.957539Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
44 of 44 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 0e82afcd-6d6d-48cb-95f1-99bf8e8e4d0b · outbound
Reference 1
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Observation 677ce0e9-a148-4977-be2f-048be66e4ec7 · outbound
Reference 2
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Observation e5fee026-0986-460d-8618-bb1ce2f4fd26 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 3
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Unavailable: canonical work link unavailable.
Observation 0d7bf459-9bf5-4494-abf7-e84f6810ab12 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 4
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Observation 222b3e58-b069-4a3f-83f2-f063585c9a79 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 5
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Observation 5fb3a231-b8ae-4d04-902c-e9b5b45eb3e8 · outbound
Reference 6
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Observation dd10f324-50f3-4517-b3c7-a10ee41de6da · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 7
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Observation 0b67dae1-1c11-4342-a5f5-544c37c5ac69 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Dynamic Origin–Destination Matrix Calibration for Large-Scale Network Simulators.Transportation Research Part C: Emerging Technologies, 2019a
Reference 8
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Observation 950d9374-2b48-4712-808f-ea91ef050569 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 9
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Observation 4b0b6997-87b5-4862-ada7-b4cae3b74b91 · outbound
Reference 10
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Observation d0508538-dc7e-43d9-8887-f716a82ce8ca · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 11
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Observation e3475b7a-4eb2-4056-a88f-63b30d2b56f0 · outbound
Reference 12
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Observation ac029355-c2e1-41e5-a391-e269211abf9d · outbound
Reference 13
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Observation 00b0058d-2073-49a2-8db4-fef59dc802eb · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Osorio.Efficient Offline Calibration of Ori- gin–Destination (Demand) for Large-Scale Stochastic Traffic Models
Reference 14
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Observation 5f2bb943-9c49-441c-8755-6c471ed344a0 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Kesting.Traffic Flow Dynamics
Reference 15
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Observation 32b48692-4065-46df-9ab0-7afd4100d08a · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Steps toward Artificial Intelligence.Proceedings of the IRE, 1961
Reference 16
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Observation 5718411b-dbfe-4b54-a177-6b9c5b198636 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment A Survey of Temporal Credit Assignment in Deep Reinforcement Learning
Reference 17
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Observation 7b627236-2461-4c79-a5d7-b27b5089613a · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 18
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Observation 8789beff-5f02-4c6f-ae53-c11b946c3a5f · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment A Brief Survey of Deep Reinforcement Learning
Reference 19
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Observation 1049e798-0652-47aa-92d2-21e7a3d1d942 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Proximal Policy Optimization Algorithms
Reference 20
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Observation 12ef41fb-f7b9-4593-8bc1-2bc593182898 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment High-Dimensional Continuous Control Using Generalized Advantage Estimation
Reference 21
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Observation 1fa94b80-8582-426b-88d9-1a821197fcea · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 22
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Observation ca59cad7-284c-4b44-877d-08103acce6a6 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 23
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Observation 7b413353-06bf-418e-80b8-9aca7a7ecfa9 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 24
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Observation 6a958d6b-f35c-427a-ac66-5305f62290f5 · outbound
Reference 25
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Observation 8e1e8422-0889-4a9b-9299-aa168721621a · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 26
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Observation 68a46a14-794c-442f-9fb0-91fec737971c · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 27
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Observation 86d265f0-ed73-49f5-aff0-9f84de8db72e · outbound
Reference 28
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Observation 0317c9b9-e440-4174-8c4e-f1ae8fb5ee58 · outbound
Reference 29
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Observation 1e1017ee-65d9-4539-bca2-99304ad67cac · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 30
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Observation 46b76a8b-96d2-46d2-b48b-c39b83c678ef · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 31
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Observation 587cb204-7748-472e-8200-198113e4dc4d · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 32
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Observation 43e9d9b3-e035-40a3-b35a-604b93d6c33a · outbound
Reference 33
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Observation a559974e-e483-4f8a-838c-6a247a58d46e · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Khoshkhah, and A
Reference 34
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Observation c2fb4ad4-7816-4cf4-889b-f5edcbf8bbcc · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 35
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Observation 880b8f0e-dcf1-4ecb-b347-458262dd4e5e · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 36
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Observation 50f11dea-88df-46c7-ac0b-33cbfb6a2074 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 37
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Observation dd34e80f-48f7-4560-86f1-60587a2fe5a0 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Value-function Approximations for Partially Ob- servable Markov Decision Processes.Journal of artificial intelligence research, 2000
Reference 38
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Observation 4797e490-440e-4379-b6a8-0fe66b5ef3cc · outbound
Reference 39
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Observation 80366d07-d79d-4e8d-939a-76be2ab7a8d2 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 40
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Observation 40811562-c89f-4b5b-b95b-9d9d01ee8089 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Playing Atari with Deep Reinforcement Learning
Reference 41
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Observation 5f782bc9-7730-4c92-9a0a-c28f9349ef86 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Unresolved cited work
Reference 42
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Observation 6a747b68-069f-4769-a3ff-4a131919dcbd · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment Springer, New York, 2010
Reference 43
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Observation 38c75a37-918a-434b-a8a4-071d03487b52 · outbound
Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment A Tutorial on Bayesian Optimization
Reference 44
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No inbound Pith citation observations are available.