Pith. sign in

Paper Citation Record · LEDGER

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes

As of 20 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2506.05953.

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

pith.paper-citation-record.v1
2506.05953 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:21:29.954534Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy2
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1af85dc5-728c-4ef0-b73e-d409453afb69 · outbound

This paper cites Continuous control with deep reinforcement learning.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes Continuous control with deep reinforcement learning

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T10:21:29.928004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:29.928004Z digest=sha256:76c431743d705f9e8c6402cbe6ef80a7ae08d8bcb75b955286be0725b0970385

Observation a224fb8b-1410-48fe-9a42-989f10280e04 · outbound

This paper cites Last-Iterate Convergence of General Parameterized Policies in Constrained MDPs.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes Last-Iterate Convergence of General Parameterized Policies in Constrained MDPs

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T10:21:29.937676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:29.937676Z digest=sha256:8a3d73ad6df6f7ec3aa777881013a5c89081fc5cb26fdef79f04644c127764e6

Observation 6091738d-e883-4ec0-96d1-66569de17fed · outbound

This paper cites an unresolved cited work.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:21:30.156809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T10:21:29.954534Z digest=sha256:31dc644354abfb9c141d39efd3f690a9e0e139f85d25ab12974da19c628e4ac7

Observation 65f17fcb-8643-478e-b787-55678502f56e · outbound

This paper cites an unresolved cited work.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:21:30.226107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T10:21:29.733240Z digest=sha256:eaaf2d96fb109c9aa32b18c3fadd8946f79bdd408e77b754a1f45a36e793cd63

Observation 1c0e0e6c-6364-41b6-b6ab-16f999295e79 · outbound

This paper cites an unresolved cited work.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes Unresolved cited work

Reference 2002

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:21:30.184116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T10:21:29.945891Z digest=sha256:7a99e8811f5429847ed67cacd1475175cc2b72a74dd3aded3032f1c75474b5a3

Observation 3bff57d4-77ba-4980-b962-88df74cf03af · outbound

This paper cites an unresolved cited work.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes Unresolved cited work

Reference 2006

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:21:30.197055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T10:21:29.941700Z digest=sha256:23a672bde67285b36e2eaae2d34eb275c1e8e309f5c4e32ae21d539a177d24c8

Observation 8e3dabbf-8f89-4c53-80c7-b30bff4f7e6c · outbound

This paper cites Policy Gradient in Partially Observable Environments: Approximation and Convergence.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes Policy Gradient in Partially Observable Environments: Approximation and Convergence

Reference 2007

Resolution
unresolved
no resolver link, observed 2026-08-07T10:21:29.414918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:29.414918Z digest=sha256:cf6397e24b881f3e27de558179ec3f91c47ee1aaa6cac5199974eb06794c6341

Observation d7531016-6d4f-4552-8e16-26323277461b · outbound

This paper cites Journal of Optimization Theory and Applications 153, 688–708.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes Journal of Optimization Theory and Applications 153, 688–708

Reference 2012

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:21:30.240836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T10:21:29.487809Z digest=sha256:54576377b4e4b8757b1ea2efc834aaef260c1a881dd93e02a88967425e0c347e

Observation 4271e805-bac3-4047-b529-7c02f71a29ea · outbound

This paper cites Safe Exploration in Continuous Action Spaces.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes Safe Exploration in Continuous Action Spaces

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-07T10:21:29.646248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:29.646248Z digest=sha256:a5604ee09cfd46eba651227260b3662977c4fc3a377b734a982dbdce93a77a1b

Observation 23eb6839-ec15-461b-983d-65b88833db7d · outbound

This paper cites Advances in Neural Information Processing Systems (NeurIPS) 33, 8378–8390.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes Advances in Neural Information Processing Systems (NeurIPS) 33, 8378–8390

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-07T10:21:29.828608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:29.828608Z digest=sha256:d03cc35044d4c4bef44250bd7fc99488d2e37de94427641e61890dce58e16c8d

Observation 701ec355-c83d-4a44-a034-63684c786d0b · outbound

This paper cites Policy Optimization for Constrained MDPs with Provable Fast Global Convergence.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes Policy Optimization for Constrained MDPs with Provable Fast Global Convergence

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-07T10:21:29.933220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:21:29.933220Z digest=sha256:87e6ed0e239d2309151f89c2aff254a4c73a9cf1e26755b697d123154ae87230

Observation 0dee27c5-8433-4924-9ad7-512cb59a7cf7 · outbound

This paper cites an unresolved cited work.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes Unresolved cited work

Reference 2022

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:21:30.170599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T10:21:29.950115Z digest=sha256:271bd6decf48fcd0e48ca394f058269d3f9c011be47c264aa13d877c8bee685b

Observation 5d26c38f-73b2-439c-9214-e1e4b74089e0 · outbound

This paper cites 11506–11533.

Learning Deterministic Policies with Policy Gradients in Constrained Markov Decision Processes 11506–11533

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:21:30.211143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T10:21:29.920865Z digest=sha256:840e4917312f42eda62bbbdaf8f1b67d5a27a93b8356143795e8ecd75d3c04ec

Pith citing papers

No inbound Pith citation observations are available.