Paper Citation Record · LEDGER

Discrete and Continuous Action Representation for Practical RL in Video Games

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1912.11077.

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

pith.paper-citation-record.v1
1912.11077 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T11:10:44.935982Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T09:16:06.702133Z

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 4e78ad1a-31ed-44ee-8487-208e809f1b19 · inbound

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark cites this paper.

Optimizing Efficiency of Mixed Traffic through Reinforcement Learning: A Topology-Independent Approach and Benchmark Discrete and Continuous Action Representation for Practical RL in Video Games

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T11:10:44.935982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 046f3757-423e-45a2-b0ea-db5b50abf7e9 · inbound

Hybrid TD3: Overestimation Bias Analysis and Stable Policy Optimization for Hybrid Action Space cites this paper.

Hybrid TD3: Overestimation Bias Analysis and Stable Policy Optimization for Hybrid Action Space Discrete and Continuous Action Representation for Practical RL in Video Games

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T19:43:50.885847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90e230b2-c91b-4ab1-92be-609c330a9b76 · inbound

Emotion Entanglement and Bayesian Inference for Multi-Dimensional Emotion Understanding cites this paper.

Emotion Entanglement and Bayesian Inference for Multi-Dimensional Emotion Understanding Discrete and Continuous Action Representation for Practical RL in Video Games

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-13T14:51:03.626575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f483c05-bcf4-40fd-978d-6fadf00d0758 · inbound

Dmsh: A Multi-Agent Reinforcement Learning Framework for All-Quad Mesh Generation cites this paper.

Dmsh: A Multi-Agent Reinforcement Learning Framework for All-Quad Mesh Generation Discrete and Continuous Action Representation for Practical RL in Video Games

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-07-03T06:37:42.896164Z

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.

Observation 86517153-6b8f-4fdf-a48c-4a2855915a8a · inbound

Revisiting Action Factorization for Complex Action Spaces cites this paper.

Revisiting Action Factorization for Complex Action Spaces Discrete and Continuous Action Representation for Practical RL in Video Games

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-04T12:59:52.062991Z

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.

Observation ca0e207e-3619-4b4c-94ac-29909f7bfe83 · inbound

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 cites this paper.

Reward-Adaptive Iterative Discovery: A Case Study on Automated Game Testing for NHL26 Discrete and Continuous Action Representation for Practical RL in Video Games

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-07-09T09:16:06.703424Z

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.