Paper Citation Record · LEDGER

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control

As of 22 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2505.09029.

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

pith.paper-citation-record.v1
2505.09029 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:45:35.150536Z

measured 24 of 24 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 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

24 of 24 outbound references displayed

verified exact0
verified fuzzy14
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b214486c-e58f-4253-8f3b-f0f7564568bf · outbound

This paper cites ”Reinforcement learning: An introduction.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”Reinforcement learning: An introduction

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.547841Z

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.

Observation cae4ee93-2c40-4817-881e-53a88a3a888f · outbound

This paper cites ”Reinforcement learning algorithms: A brief survey.” Expert Systems with Applications 231 (2023): 120495.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”Reinforcement learning algorithms: A brief survey.” Expert Systems with Applications 231 (2023): 120495

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.533228Z

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.

Observation 9e7cba20-a200-4130-adee-723c7eba24cd · outbound

This paper cites ”Using reinforcement learning for load testing of video games.” Proceedings of the 44th international conference on software engineering.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”Using reinforcement learning for load testing of video games.” Proceedings of the 44th international conference on software engineering

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.517836Z

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.

Observation 6c3251f6-180d-4827-8cb1-ca76e7cd2591 · outbound

This paper cites ”A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management.” Information Fusion (2024): 102369.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management.” Information Fusion (2024): 102369

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.503172Z

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.

Observation 30fd499a-75dc-4bcf-b16c-6153aecc0ae8 · outbound

This paper cites an unresolved cited work.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:45:35.488101Z

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.

Observation 0184d00b-5bf5-4fab-ac08-c62caccdaf01 · outbound

This paper cites MuJoCo Playground.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control MuJoCo Playground

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T21:45:35.064770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af29866b-345d-4b86-af39-4cf23f056e9f · outbound

This paper cites ”Continuous control actions learning and adaptation for robotic manipulation through reinforcement learning.” Autonomous Robots 46.3 (2022): 483-498.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”Continuous control actions learning and adaptation for robotic manipulation through reinforcement learning.” Autonomous Robots 46.3 (2022): 483-498

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.472673Z

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.

Observation b5f35a32-d0f8-405b-92c3-84355e64a4ed · outbound

This paper cites ”Deep deterministic policy gradient algorithm: A systematic review.” Heliyon (2024).

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”Deep deterministic policy gradient algorithm: A systematic review.” Heliyon (2024)

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.455950Z

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.

Observation 503de0fe-97cc-423e-8862-ca89dfbd3465 · outbound

This paper cites ”Addressing function approximation error in actor-critic methods.” International conference on machine learning.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”Addressing function approximation error in actor-critic methods.” International conference on machine learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.439305Z

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.

Observation 2020f5a2-5dac-4227-b83e-ced049cbbba8 · outbound

This paper cites ”Stable-baselines3: Reliable reinforcement learning implementations.” Journal of machine learning research 22.268 (2021): 1-8.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”Stable-baselines3: Reliable reinforcement learning implementations.” Journal of machine learning research 22.268 (2021): 1-8

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.421564Z

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.

Observation c9a48528-1cfa-4590-a1cd-9d4ee9ef4617 · outbound

This paper cites Eyes on the Environment: AI-Driven Analysis for Fire and Smoke Classification, Segmentation, and Detection.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control Eyes on the Environment: AI-Driven Analysis for Fire and Smoke Classification, Segmentation, and Detection

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T21:45:35.088192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ce57820-9eae-4921-ad16-ec3d785ba5c2 · outbound

This paper cites Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.404273Z

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.

Observation eda5f139-b497-4678-85be-b4cc802f87e9 · outbound

This paper cites ”AlphaZero.” Deep Reinforce- ment Learning: Fundamentals, Research and Applications (2020): 391- 415.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”AlphaZero.” Deep Reinforce- ment Learning: Fundamentals, Research and Applications (2020): 391- 415

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.387544Z

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.

Observation 866b4b9a-3db6-4e01-aa06-335aa0eef24b · outbound

This paper cites Automatic Prompt Optimization with "Gradient Descent" and Beam Search.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control Automatic Prompt Optimization with "Gradient Descent" and Beam Search

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T21:45:35.101965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8ccdd19-8117-4251-94a3-3953d7dbfa9b · outbound

This paper cites ”Simulation-guided beam search for neural com- binatorial optimization.” Advances in Neural Information Processing Systems 35 (2022): 8760-8772.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”Simulation-guided beam search for neural com- binatorial optimization.” Advances in Neural Information Processing Systems 35 (2022): 8760-8772

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.371794Z

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.

Observation 43d36889-2ea1-4806-b25b-77e502231a41 · outbound

This paper cites ”Monte Carlo tree search: A review of recent modifications and applications.” Artificial Intelligence Review 56.3 (2023): 2497-2562.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”Monte Carlo tree search: A review of recent modifications and applications.” Artificial Intelligence Review 56.3 (2023): 2497-2562

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.356588Z

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.

Observation ae813dbc-8b2a-44ac-b6b5-de339479dfe9 · outbound

This paper cites Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T21:45:35.115772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0315eb13-f23d-43cc-b771-cc935a2af31d · outbound

This paper cites ”Beyond greedy search: Tracking by multi-agent reinforcement learning-based beam search.” IEEE Transactions on Image Processing 31 (2022): 6239-6254.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”Beyond greedy search: Tracking by multi-agent reinforcement learning-based beam search.” IEEE Transactions on Image Processing 31 (2022): 6239-6254

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.341152Z

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.

Observation b68f52c9-d7ec-4cfe-9954-f33d97a001dd · outbound

This paper cites ”RL Baselines3 Zoo.” GitHub repository (2020).

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control ”RL Baselines3 Zoo.” GitHub repository (2020)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:45:35.323678Z

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.

Observation d34cd3fe-9512-440a-9675-026d56de3c96 · outbound

This paper cites OpenAI Gym.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control OpenAI Gym

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T21:45:35.130093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7f1d474-7272-4cd3-8e9b-0d075b2ae5aa · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control Soft Actor-Critic Algorithms and Applications

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T21:45:35.134938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 845e944e-000f-4355-ab96-3c7494df062e · outbound

This paper cites A2C is a special case of PPO.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control A2C is a special case of PPO

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T21:45:35.140853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6dbc1c6b-53ec-47bd-be34-3cf5cfb4fa7a · outbound

This paper cites Proximal Policy Optimization Algorithms.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control Proximal Policy Optimization Algorithms

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T21:45:35.146067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff361cf6-bfb1-4f83-8c13-456afcea3f27 · outbound

This paper cites VisionGPT: LLM-Assisted Real-Time Anomaly Detection for Safe Visual Navigation.

Monte Carlo Beam Search for Actor-Critic Reinforcement Learning in Continuous Control VisionGPT: LLM-Assisted Real-Time Anomaly Detection for Safe Visual Navigation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T21:45:35.150536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.