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Paper Citation Record · LEDGER

Multi Agent Path Finding using Evolutionary Game Theory

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2212.02010.

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

pith.paper-citation-record.v1
2212.02010 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:20:18.012983Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:20:20.267939Z

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 7e006c41-b4bd-44d5-99d4-23e6e9723200 · inbound

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding cites this paper.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Multi Agent Path Finding using Evolutionary Game Theory

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:20:20.320352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:20:18.012983Z digest=sha256:c9423223e2d6ac01aeff719ec8e82a88ae2eb4ef8145df9db06f95ba544f5f0c

Observation ff2e1604-8800-4cf4-989f-b7765c3eef26 · inbound

Adaptive-Horizon Conflict-Based Search for Closed-Loop Multi-Agent Path Finding cites this paper.

Adaptive-Horizon Conflict-Based Search for Closed-Loop Multi-Agent Path Finding Multi Agent Path Finding using Evolutionary Game Theory

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-03T00:03:07.790414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T00:03:07.790414Z digest=sha256:a4c757723a7192352b91fd7f6444535a8cd9d89dd74969328a7c6954dc827533