Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Achieving Fairness in Multi-Agent Markov Decision Processes Using Reinforcement Learning
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2306.00324.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T19:37:03.117742Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-27T05:20:35.879203Z
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 8eacde2d-cf0a-4a88-9d77-5dc8b05a3aa8 · inbound
Fairness in Reinforcement Learning with Bisimulation Metrics cites this paper.
Fairness in Reinforcement Learning with Bisimulation Metrics Achieving Fairness in Multi-Agent Markov Decision Processes Using Reinforcement Learning
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:52:34.516784Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4b0f8025-f4d4-429f-9518-de7dfdf6e291 · inbound
Fair Contracts in Principal-Agent Games with Heterogeneous Types cites this paper.
Fair Contracts in Principal-Agent Games with Heterogeneous Types Achieving Fairness in Multi-Agent Markov Decision Processes Using Reinforcement Learning
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:37:03.117742Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 515bcbbc-d28e-4f67-9994-a817ee534da0 · inbound
$\alpha$-fair heterogeneous agent reinforcement learning cites this paper.
$\alpha$-fair heterogeneous agent reinforcement learning Achieving Fairness in Multi-Agent Markov Decision Processes Using Reinforcement Learning
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-06-27T05:20:35.880721Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.