Paper Citation Record · LEDGER

Proactive Constrained Policy Optimization with Preemptive Penalty

As of 16 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2508.01883.

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

pith.paper-citation-record.v1
2508.01883 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:26:41.702511Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

33 of 33 outbound references displayed

verified exact0
verified fuzzy22
unresolved10
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 158c1d0a-84f8-4e6d-a6f6-822a4f06fc5f · outbound

This paper cites Safe exploration in continuous action spaces, 2018.

Proactive Constrained Policy Optimization with Preemptive Penalty Safe exploration in continuous action spaces, 2018

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:45.597366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8c770962-57f9-42a2-a67b-b091b3d94b69 · outbound

This paper cites A lyapunov-based approach to safe reinforcement learning.

Proactive Constrained Policy Optimization with Preemptive Penalty A lyapunov-based approach to safe reinforcement learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T05:26:38.856977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9107fa5c-4e99-473c-8222-a1263edd31d0 · outbound

This paper cites Lyapunov-based safe reinforcement learning for microgrid energy management.IEEE transactions on neural networks and learning systems, 2024.

Proactive Constrained Policy Optimization with Preemptive Penalty Lyapunov-based safe reinforcement learning for microgrid energy management.IEEE transactions on neural networks and learning systems, 2024

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:45.400330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7cb9a1bb-0a77-456a-93c4-7d1eb72ba55e · outbound

This paper cites Reward Constrained Policy Optimization.

Proactive Constrained Policy Optimization with Preemptive Penalty Reward Constrained Policy Optimization

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T05:26:39.090493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d7809c2-a09d-4131-add5-db0c898de8be · outbound

This paper cites A review of safe reinforcement learning: Methods, theories and applications.

Proactive Constrained Policy Optimization with Preemptive Penalty A review of safe reinforcement learning: Methods, theories and applications

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T05:26:39.201603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfdbf03e-c4e2-4a24-9ec1-0a616736697b · outbound

This paper cites Cvar-constrained policy optimization for safe reinforcement learning.

Proactive Constrained Policy Optimization with Preemptive Penalty Cvar-constrained policy optimization for safe reinforcement learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:45.212121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 25954455-b329-4f15-853e-1ab49c69c1cd · outbound

This paper cites Safe reinforcement learning for multi-agent systems with risk constraints.

Proactive Constrained Policy Optimization with Preemptive Penalty Safe reinforcement learning for multi-agent systems with risk constraints

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:45.017761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 21b67990-3376-4db2-b984-bbac0bf513a4 · outbound

This paper cites Lyapunov-based safe policy optimization for continuous control, 2019.

Proactive Constrained Policy Optimization with Preemptive Penalty Lyapunov-based safe policy optimization for continuous control, 2019

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:44.769847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 17118456-c96d-4c44-b024-1d6d4f6219be · outbound

This paper cites Responsive safety in reinforcement learning by pid lagrangian methods.

Proactive Constrained Policy Optimization with Preemptive Penalty Responsive safety in reinforcement learning by pid lagrangian methods

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T05:26:39.672273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35880f46-6317-4f9a-8698-05ac91fbb800 · outbound

This paper cites Soufi Enayati, Mehran Ghafarian Tamizi, and Homayoun Najjaran.

Proactive Constrained Policy Optimization with Preemptive Penalty Soufi Enayati, Mehran Ghafarian Tamizi, and Homayoun Najjaran

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:44.588775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dc73e218-5bfb-4075-89f4-7853786c8c85 · outbound

This paper cites A survey of constraint formulations in safe reinforcement learning, 2024.

Proactive Constrained Policy Optimization with Preemptive Penalty A survey of constraint formulations in safe reinforcement learning, 2024

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:44.430941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 69baed02-188c-4f37-84b3-29394e97d553 · outbound

This paper cites Projection-Based Constrained Policy Optimization.

Proactive Constrained Policy Optimization with Preemptive Penalty Projection-Based Constrained Policy Optimization

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T05:26:39.944282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c184f696-0fc4-4987-91df-61f0d986fd55 · outbound

This paper cites Risk-constrained reinforcement learning with percentile risk criteria.

Proactive Constrained Policy Optimization with Preemptive Penalty Risk-constrained reinforcement learning with percentile risk criteria

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:44.278532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1d51875b-3f80-43d4-a743-6fa57a6b21ab · outbound

This paper cites Constrained policy optimization.

Proactive Constrained Policy Optimization with Preemptive Penalty Constrained policy optimization

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T05:26:40.158865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 712f9f21-044c-4653-8c19-b3b69a38efb9 · outbound

This paper cites Safe reinforcement learning using advantage-based intervention.

Proactive Constrained Policy Optimization with Preemptive Penalty Safe reinforcement learning using advantage-based intervention

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:44.152979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1223e959-01da-4f0f-95b3-0f492f85ad12 · outbound

This paper cites Provably efficient primal-dual reinforcement learning for cmdps with non-stationary objectives and constraints.

Proactive Constrained Policy Optimization with Preemptive Penalty Provably efficient primal-dual reinforcement learning for cmdps with non-stationary objectives and constraints

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:43.998691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 90958591-c93f-48bf-acba-838bfe795348 · outbound

This paper cites Scalable primal- dual actor-critic method for safe multi-agent rl with general utilities.

Proactive Constrained Policy Optimization with Preemptive Penalty Scalable primal- dual actor-critic method for safe multi-agent rl with general utilities

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:43.903161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fbf3189f-7c34-49e7-aee6-a0dcf555708d · outbound

This paper cites Adaptive primal-dual method for safe reinforce- ment learning, 2024.

Proactive Constrained Policy Optimization with Preemptive Penalty Adaptive primal-dual method for safe reinforce- ment learning, 2024

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:43.771070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation abb19f79-54c5-445b-a110-6ecf2a944da9 · outbound

This paper cites Balance reward and safety optimization for safe reinforcement learning: A perspective of gradient manipulation.

Proactive Constrained Policy Optimization with Preemptive Penalty Balance reward and safety optimization for safe reinforcement learning: A perspective of gradient manipulation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:43.612791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bd75ed25-de71-418e-8265-a3878072853d · outbound

This paper cites Safe cor: A dual-expert approach to integrating imitation learning and safe reinforcement learning using constraint rewards.

Proactive Constrained Policy Optimization with Preemptive Penalty Safe cor: A dual-expert approach to integrating imitation learning and safe reinforcement learning using constraint rewards

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:43.462053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4f735d69-43ea-4c44-b06e-f32235da32ee · outbound

This paper cites Safe reinforcement learning via episodic control.

Proactive Constrained Policy Optimization with Preemptive Penalty Safe reinforcement learning via episodic control

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:43.327459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 730a5251-5b7c-405b-93a1-3c6824cdfb27 · outbound

This paper cites Comprehensive overview of reward engineering and shaping in advancing reinforcement learning applications.

Proactive Constrained Policy Optimization with Preemptive Penalty Comprehensive overview of reward engineering and shaping in advancing reinforcement learning applications

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:43.126303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3e5e93af-91a8-42d0-bd39-283a535f8cff · outbound

This paper cites A review of safe reinforcement learning methods for modern power systems.

Proactive Constrained Policy Optimization with Preemptive Penalty A review of safe reinforcement learning methods for modern power systems

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:42.946267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7f434828-22fa-4faf-aad4-c3659ecf033c · outbound

This paper cites Constrained Markov decision processes.

Proactive Constrained Policy Optimization with Preemptive Penalty Constrained Markov decision processes

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T05:26:41.098054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f0ee32c-7a79-4a4e-b7d0-8b28b8b53bbf · outbound

This paper cites Reinforcement learning, 2015.

Proactive Constrained Policy Optimization with Preemptive Penalty Reinforcement learning, 2015

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:42.769405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c2a75454-4b9a-4462-9e1c-b6d578cdd7b6 · outbound

This paper cites Asynchronous methods for deep reinforce- ment learning.

Proactive Constrained Policy Optimization with Preemptive Penalty Asynchronous methods for deep reinforce- ment learning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T05:26:41.251357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96babdb9-16e3-42da-8e6c-e4d1a9a1d8f9 · outbound

This paper cites Constrained deep networks: Lagrangian optimization via log-barrier extensions.

Proactive Constrained Policy Optimization with Preemptive Penalty Constrained deep networks: Lagrangian optimization via log-barrier extensions

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T05:26:41.316580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8189934b-557a-43e5-aa0b-eafd085a65df · outbound

This paper cites A tutorial on mm algorithms.

Proactive Constrained Policy Optimization with Preemptive Penalty A tutorial on mm algorithms

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:42.576444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2cc1ca94-bbdd-476f-98c4-5d4883ce31e4 · outbound

This paper cites Safety gymnasium: A unified safe reinforcement learning benchmark.

Proactive Constrained Policy Optimization with Preemptive Penalty Safety gymnasium: A unified safe reinforcement learning benchmark

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:42.435045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9eac2dca-eb20-4493-b0ca-fde350a1a3be · outbound

This paper cites Constrained update projection approach to safe policy optimization.

Proactive Constrained Policy Optimization with Preemptive Penalty Constrained update projection approach to safe policy optimization

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:42.315793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 60bb6ac8-e7bf-4a41-8bcc-a64de835a208 · outbound

This paper cites First order constrained optimization in policy space.

Proactive Constrained Policy Optimization with Preemptive Penalty First order constrained optimization in policy space

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:26:42.162364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 91f14207-99f6-4e88-ad5d-3f74c8fcc513 · outbound

This paper cites Trust region policy optimization.

Proactive Constrained Policy Optimization with Preemptive Penalty Trust region policy optimization

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T05:26:41.646373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7862b4c-a11e-45be-8c1c-e40d78bea53d · outbound

This paper cites repulsive force.

Proactive Constrained Policy Optimization with Preemptive Penalty repulsive force

Reference 33

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T05:26:41.994351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

No inbound Pith citation observations are available.