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Paper Citation Record · LEDGER

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints

As of 22 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 1 inbound Pith citation observation for arXiv:2412.04327.

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

pith.paper-citation-record.v1
2412.04327 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:39:12.005657Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:00:05.718655Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T22:00:05.830885Z

Reference resolution

17 of 17 outbound references displayed

  • verified exact2
  • verified fuzzy2
  • unresolved12
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 97fd7f80-2c1c-4987-8a9b-6814ec00a16a · outbound

This paper cites Safe Exploration in Continuous Action Spaces.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints Safe Exploration in Continuous Action Spaces

Reference 3

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unresolved
no resolver link, observed 2026-08-11T21:39:11.928666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.928666Z digest=sha256:5a4b30a0c774fdfa0c166bd908d98f4aa3a2cea2bab16c14535844f3eac38a53

Observation 05999720-a7d4-4a56-9c5c-e66a0a6ebcc1 · outbound

This paper cites Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise Safety

Reference 8

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no resolver link, observed 2026-08-11T21:39:11.955651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.955651Z digest=sha256:83746c87f0d22f53e70af86c25c315c90da6dee3eeaf29174984bf8ee965e95b

Observation 96f35f8a-f1fd-4bb7-b509-1ae6ea2e49c5 · outbound

This paper cites Benchmarking Batch Deep Reinforcement Learning Algorithms.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints Benchmarking Batch Deep Reinforcement Learning Algorithms

Reference 9

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no resolver link, observed 2026-08-11T21:39:11.960949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.960949Z digest=sha256:41603e10c57e30e9e59a3c01bf89429214970602b9c4d2bc937510b9534f7b7b

Observation 6a1a3f2b-7fd3-4ba6-ac6a-352b744262ee · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 10

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unresolved
no resolver link, observed 2026-08-11T21:39:11.966125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.966125Z digest=sha256:a5504a86bf24e1f6699df3a9eb70b5de184113ee50e5b3b673c35cf08fa7fb0d

Observation d8bcd68a-5b75-45fe-9f23-fe56df76a5a0 · outbound

This paper cites Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints Excluding the Irrelevant: Focusing Reinforcement Learning through Continuous Action Masking

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-11T21:39:12.111309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T21:39:11.982996Z digest=sha256:52a72230f3be84c4389957fbf5e69d6c4d5a45095107d578b5750f6bc702eeae

Observation 083d31d0-75dc-4126-bd6a-00f468607559 · outbound

This paper cites RaceMOP: Mapless Online Path Planning for Multi-Agent Autonomous Racing using Residual Policy Learning.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints RaceMOP: Mapless Online Path Planning for Multi-Agent Autonomous Racing using Residual Policy Learning

Reference 14

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verified exact
local_arxiv, observed 2026-08-11T21:39:12.086025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T21:39:11.988838Z digest=sha256:fdb060461e5bf171dd47742f06664fcfc32b4f25a7343652c1520bd5bb65f3d9

Observation 2187593e-e1e6-4cd9-b695-80d81a08ed3d · outbound

This paper cites Penalized Proximal Policy Optimization for Safe Reinforcement Learning.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints Penalized Proximal Policy Optimization for Safe Reinforcement Learning

Reference 15

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no resolver link, observed 2026-08-11T21:39:11.994473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.994473Z digest=sha256:4ecb7ec45ee48fbde906d22d029b9d59f7ea140bfe386d7de7875083bb1d6fda

Observation d53b5711-1645-427e-84c0-ffa6c9bbe208 · outbound

This paper cites an unresolved cited work.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints Unresolved cited work

Reference 17

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malformed identifier
raw_fallback, observed 2026-08-11T21:39:12.294747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T21:39:12.005657Z digest=sha256:fc44711ff5e38d3279ddd84a9c455d8de5900af1a8ca61f9a24e93ba641d4c5d

Observation 9ec14cd6-f8f0-4220-b0b0-ed3bc72dc424 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints Proximal Policy Optimization Algorithms

Reference 2015

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unresolved
no resolver link, observed 2026-08-11T21:39:11.972205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.972205Z digest=sha256:d78dd43c8034e3a0fda8771a2e1c0bd7a45c493513197eb73173aa4218ab45b1

Observation 34ee1234-8034-48d5-894a-9d9845beab7a · outbound

This paper cites Learning to be Safe: Deep RL with a Safety Critic.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints Learning to be Safe: Deep RL with a Safety Critic

Reference 2017

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no resolver link, observed 2026-08-11T21:39:11.977292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.977292Z digest=sha256:3e944068280c1f7eb8307680aa5560e365d359ae65ba55a5242911210421a538

Observation c50f1d80-fa3f-41ac-af74-e2ad62556fc9 · outbound

This paper cites A Closer Look at Invalid Action Masking in Policy Gradient Algorithms.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints A Closer Look at Invalid Action Masking in Policy Gradient Algorithms

Reference 2018

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unresolved
no resolver link, observed 2026-08-11T21:39:11.945279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.945279Z digest=sha256:ff65b28399ba28bd24306e96ba88453eb2dab050973884d1d6692fbe4f142f77

Observation 8feeebb4-3998-42f7-9843-17fff94009c1 · outbound

This paper cites Lyapunov-based Safe Policy Optimization for Continuous Control.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints Lyapunov-based Safe Policy Optimization for Continuous Control

Reference 2019

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no resolver link, observed 2026-08-11T21:39:11.923300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.923300Z digest=sha256:07335d2e8f94952b85e369cce13119af8c3b3ea84d723de949e48b661f7ef943

Observation e0592a37-9612-4e8e-9015-700333029c65 · outbound

This paper cites Safe reinforcement learning for autonomous lane changing using set-based prediction.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints Safe reinforcement learning for autonomous lane changing using set-based prediction

Reference 2020

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verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.311768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T21:39:11.950595Z digest=sha256:ad8cbc52aba78fea991ef0da1fa98ebb1ef45f620d391ad2e25f6f290a0fd78c

Observation bd1b9821-a7db-4cbd-9802-90cf01a2c2b9 · outbound

This paper cites Conservative Safety Critics for Exploration.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints Conservative Safety Critics for Exploration

Reference 2021

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no resolver link, observed 2026-08-11T21:39:11.917036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.917036Z digest=sha256:e7e6a827a5a8988d00b128b20de737959813cd17a7154004ede1246d0ae70bb6

Observation 1a9e4239-f93f-40a9-9e5a-a294b0382eac · outbound

This paper cites A Review of Safe Reinforcement Learning: Methods, Theory and Applications.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Reference 2022

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unresolved
no resolver link, observed 2026-08-11T21:39:11.939149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.939149Z digest=sha256:9d7a12d3bbd4910df30e8e5a62feefe5032781a90d4c786c5f5fe77ddc6fbc9b

Observation 350272cd-c349-4cbb-a677-6fefca8699a8 · outbound

This paper cites State-wise Safe Reinforcement Learning: A Survey.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints State-wise Safe Reinforcement Learning: A Survey

Reference 2023

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no resolver link, observed 2026-08-11T21:39:11.999964Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T21:39:11.999964Z digest=sha256:2d3bc1fad3bc782177b1f003ee6116e549c3041865b6f5c5586b7f15075c6b64

Observation ead9282f-7d07-40b5-a522-5db4c326d1ea · outbound

This paper cites Niklas Funk, Georgia Chalvatzaki, Boris Belousov, and Jan Peters.

Action Mapping for Reinforcement Learning in Continuous Environments with Constraints Niklas Funk, Georgia Chalvatzaki, Boris Belousov, and Jan Peters

Reference 2024

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verified fuzzy
raw_fallback, observed 2026-08-11T21:39:12.327333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-11T21:39:11.934161Z digest=sha256:0c8cb637ff4514880e19db6352ead50793b1167c0714e28846a746fc5ee08a99

Pith citing papers

Observation 49af79bd-6ed1-483c-a1b1-558e5fd892db · inbound

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning cites this paper.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Action Mapping for Reinforcement Learning in Continuous Environments with Constraints

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-15T22:00:05.839360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T22:00:05.718655Z digest=sha256:42ff202ac610143f64368bc5bc1fcb159fa6734151d9f01951dd6720e361812b