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Paper Citation Record · LEDGER

Model-based Reinforcement Learning: A Survey

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2006.16712.

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

pith.paper-citation-record.v1
2006.16712 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T01:04:38.609510Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T20:37:34.104637Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 82c3ec8c-fcbd-4cba-913a-2cb120c18cfd · inbound

A Review of Cooperative Multi-Agent Deep Reinforcement Learning cites this paper.

A Review of Cooperative Multi-Agent Deep Reinforcement Learning Model-based Reinforcement Learning: A Survey

Reference 119

Resolution
unresolved
no resolver link, observed 2026-08-14T13:59:09.326537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:59:09.326537Z digest=sha256:b539ede926281b0d034be6b0a38c6c39b36aff00959ceb7f399fabedbc5693f7

Observation 9778ed31-dae6-45a9-afae-75edd99bc68a · inbound

Survey on safe robot control via learning cites this paper.

Survey on safe robot control via learning Model-based Reinforcement Learning: A Survey

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-11T14:13:09.018910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:13:09.018910Z digest=sha256:d5ba8999849a437fd67f9fb4b27ea811ff92a9ccff354b25e026e13c1bfde52a

Observation acf57ae0-2144-4c3b-8141-be2b610886fc · inbound

Improving Transformer World Models for Data-Efficient RL cites this paper.

Improving Transformer World Models for Data-Efficient RL Model-based Reinforcement Learning: A Survey

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-09T14:59:44.989171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:59:44.989171Z digest=sha256:8e2b92b4d79bf07eb3bf4de2b8619acff26eeec8cd52914dd3bf390238d07505

Observation ef2b4856-8ffe-4771-98b3-c7a4418d7204 · inbound

LLM-Guided Probabilistic Program Induction for POMDP Model Estimation cites this paper.

LLM-Guided Probabilistic Program Induction for POMDP Model Estimation Model-based Reinforcement Learning: A Survey

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T01:04:38.609510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T01:04:38.609510Z digest=sha256:66cbc75431e923adfb8489b32caf39060259e4b2f7e74e17ea2343e7fbbe23c9

Observation 25dfb52f-4a83-4a43-a434-0e93b6c56e3a · inbound

Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review cites this paper.

Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review Model-based Reinforcement Learning: A Survey

Reference 147

Resolution
unresolved
no resolver link, observed 2026-08-15T22:17:41.070322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:17:41.070322Z digest=sha256:ab9d93b9e2850d4452e51bf44e098d6af53dc0db282c4ea969b31892f8d584fb

Observation cc974e25-ff59-48dd-9d1b-02cd69e16eca · inbound

Model-free Reinforcement Learning for Model-based Control: Towards Safe, Interpretable and Sample-efficient Agents cites this paper.

Model-free Reinforcement Learning for Model-based Control: Towards Safe, Interpretable and Sample-efficient Agents Model-based Reinforcement Learning: A Survey

Reference 128

Resolution
unresolved
no resolver link, observed 2026-08-06T16:28:58.403785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:28:58.403785Z digest=sha256:3158b1e1525e33a8814dfce1e24c8166d652af7ef9373a6fa81983110b20b9b0

Observation 57ede97e-27cf-4f11-b2f7-a0360a63cba9 · inbound

Temporal Basis Function Models for Closed-Loop Neural Stimulation cites this paper.

Temporal Basis Function Models for Closed-Loop Neural Stimulation Model-based Reinforcement Learning: A Survey

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T15:41:59.924682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:41:59.924682Z digest=sha256:0b75be620c4eab3528ff1cd9f8695321a457e536e32684fae2eb9b7d5a8bc7cc

Observation af4e4fec-62aa-4c5f-9cb9-6cfcd635bc95 · inbound

Learning Ad Hoc Network Dynamics via Graph-Structured World Models cites this paper.

Learning Ad Hoc Network Dynamics via Graph-Structured World Models Model-based Reinforcement Learning: A Survey

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-10T12:05:22.313929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T12:02:12.857242Z digest=sha256:3c3137098de0149fdd3346b4043d47033458beca166f2bd04d159ad9520ddfe2

Observation e474e7f6-fa1d-4cd9-b922-df3b68bd45c1 · inbound

UBP2: Uncertainty-Balanced Preference Planning for Efficient Preference-based Reinforcement Learning cites this paper.

UBP2: Uncertainty-Balanced Preference Planning for Efficient Preference-based Reinforcement Learning Model-based Reinforcement Learning: A Survey

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T00:09:14.907252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-26T21:27:31.026539Z digest=sha256:b839b73f293ca36141e211724235b5deff0f83ecb67d4c2c4e7b22b5aa11ae5f

Observation b962d3f6-d0fa-4f4c-80ec-a7a1311c0a14 · inbound

Solving Markov Decision Processes with Future Information via MPC cites this paper.

Solving Markov Decision Processes with Future Information via MPC Model-based Reinforcement Learning: A Survey

Reference 68

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T19:00:06.260425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-25T22:00:02.577707Z digest=sha256:8d6590f13b4dd0ea3da5c6aa73d97a5a9f0da2577910e3a6969d56f12d5f0420

Observation 1c13e5a2-ced5-41a3-9464-9b59b8d32ebc · inbound

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts cites this paper.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Model-based Reinforcement Learning: A Survey

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-07-10T20:37:34.106345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-07-10T20:34:14.693049Z digest=sha256:5fae4402b847364a860ecc40d48c87a778925b4c138bc60bd75255f5c7e67c78

Observation 18006a6e-3f60-4329-8972-1c6e5fccadb0 · inbound

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts cites this paper.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Model-based Reinforcement Learning: A Survey

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-02T08:18:13.594573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T08:18:13.594573Z digest=sha256:e089a29590aed264f0afe98ba06ebbd535495ad8bb10da4182dab90a846461b4

Observation d5758318-51ce-4909-bd4d-b081eeee91c9 · inbound

PhyAgentOS: A Self-Evolving Operating System for Embodied Agents with Decoupled Cognitive Planning and Physical Execution cites this paper.

PhyAgentOS: A Self-Evolving Operating System for Embodied Agents with Decoupled Cognitive Planning and Physical Execution Model-based Reinforcement Learning: A Survey

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-01T20:28:19.676070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T20:28:19.676070Z digest=sha256:ff014330a8869b3a81f6e0876ce4fd397457c1091751b11dbda1a20dc675c236