Paper Citation Record · LEDGER

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

As of 11 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2505.19219.

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

pith.paper-citation-record.v1
2505.19219 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:20:18.987183Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-23T02:03:47.244209Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T02:05:19.509866Z

Reference resolution

29 of 29 outbound references displayed

verified exact11
verified fuzzy6
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dfb277bb-8cd6-40e1-b17b-682d376615bd · outbound

This paper cites Odrm* optimal multirobot path plan- ning in low dimensional search spaces.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Odrm* optimal multirobot path plan- ning in low dimensional search spaces

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:20:21.995003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b78f58d8-3e88-4e50-b540-3083e5adb3fa · outbound

This paper cites Social Behavior as a Key to Learning-based Multi-Agent Pathfinding Dilemmas.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Social Behavior as a Key to Learning-based Multi-Agent Pathfinding Dilemmas

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:20:21.020894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 58361718-96d4-4821-a2cc-317fb00c7498 · outbound

This paper cites Formalization of Optimality Conditions for Smooth Constrained Optimization Problems.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Formalization of Optimality Conditions for Smooth Constrained Optimization Problems

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:17.064529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c2142cb-a13d-493c-a3f5-33d1cd687e0d · outbound

This paper cites Multi-Agent Target Assignment and Path Finding for Intelligent Warehouse: A Cooperative Multi-Agent Deep Reinforcement Learning Perspective.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Multi-Agent Target Assignment and Path Finding for Intelligent Warehouse: A Cooperative Multi-Agent Deep Reinforcement Learning Perspective

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:17.394115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1683716c-45e9-40d5-94c4-add1a99b62ae · outbound

This paper cites Lifelong Multi-Agent Path Finding for Online Pickup and Delivery Tasks.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Lifelong Multi-Agent Path Finding for Online Pickup and Delivery Tasks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:17.490938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a634e927-9015-4928-9217-6413656ac55b · outbound

This paper cites Flatland-RL : Multi-Agent Reinforcement Learning on Trains.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Flatland-RL : Multi-Agent Reinforcement Learning on Trains

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:17.624351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 928d5bad-3f1c-457f-a701-9dee3a73c0ae · outbound

This paper cites Improving LaCAM for Scalable Eventually Optimal Multi-Agent Pathfinding.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Improving LaCAM for Scalable Eventually Optimal Multi-Agent Pathfinding

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:20:20.710669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5299c64e-8d16-4d58-b320-80cd5ad0b5c6 · outbound

This paper cites winPIBT: Extended Prioritized Algorithm for Iterative Multi-agent Path Finding.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding winPIBT: Extended Prioritized Algorithm for Iterative Multi-agent Path Finding

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:20:20.579937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7e006c41-b4bd-44d5-99d4-23e6e9723200 · outbound

This paper cites Multi Agent Path Finding using Evolutionary Game Theory.

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 2026-08-10T06:31:04.303077+00:00.

Observation 6a867521-a2df-44b0-b4b2-a0956c7f4129 · outbound

This paper cites Confidence-Based Curriculum Learning for Multi-Agent Path Finding.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Confidence-Based Curriculum Learning for Multi-Agent Path Finding

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:20:20.173975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9ede09fa-f5a9-4aff-8cf1-62b209db12c9 · outbound

This paper cites Multi-agent navigation based on deep reinforcement learning and traditional pathfinding algorithm.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Multi-agent navigation based on deep reinforcement learning and traditional pathfinding algorithm

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:20:20.032582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0e395897-4864-47a2-b562-63e671047807 · outbound

This paper cites MAPFAST: A Deep Algorithm Selector for Multi Agent Path Finding using Shortest Path Embeddings.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding MAPFAST: A Deep Algorithm Selector for Multi Agent Path Finding using Shortest Path Embeddings

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:20:19.913009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4293428d-4f2f-4acc-a09e-a32d35bdd65f · outbound

This paper cites LLMDR: LLM-Driven Deadlock Detection and Resolution in Multi-Agent Pathfinding.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding LLMDR: LLM-Driven Deadlock Detection and Resolution in Multi-Agent Pathfinding

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:18.362271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24fde042-6bf6-4a0d-b6a4-a22220d28497 · outbound

This paper cites Automatic Algorithm Selection In Multi-agent Pathfinding.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Automatic Algorithm Selection In Multi-agent Pathfinding

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:20:19.745297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 96f940d7-249e-4ec9-a9f1-011e2d5fadee · outbound

This paper cites POGEMA: A Benchmark Platform for Cooperative Multi-Agent Pathfinding.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding POGEMA: A Benchmark Platform for Cooperative Multi-Agent Pathfinding

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:18.526685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20663c9a-4c9f-4936-beb9-82b8afad35db · outbound

This paper cites Reevaluation of Large Neighborhood Search for MAPF: Findings and Opportunities.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Reevaluation of Large Neighborhood Search for MAPF: Findings and Opportunities

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:20:19.399604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7e9a7097-30a1-45b8-8d1a-1d6d2ba52413 · outbound

This paper cites Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:18.775994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7629778c-1ebc-4642-9c78-d6a525aa491a · outbound

This paper cites M*: A complete multirobot path planning algorithm with performance bounds.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding M*: A complete multirobot path planning algorithm with performance bounds

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:20:21.394136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation decdae40-8fa6-4c67-ba2d-f7112c8a436e · outbound

This paper cites LNS2+RL: Combining Multi-Agent Reinforcement Learning with Large Neighborhood Search in Multi-Agent Path Finding.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding LNS2+RL: Combining Multi-Agent Reinforcement Learning with Large Neighborhood Search in Multi-Agent Path Finding

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:20:19.207331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7a2ac8c6-6b36-48a7-9eb3-9d4fba257dd4 · outbound

This paper cites Perceive, Reflect, and Plan: Designing LLM Agent for Goal-Directed City Navigation without Instructions.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Perceive, Reflect, and Plan: Designing LLM Agent for Goal-Directed City Navigation without Instructions

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:18.987183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c03aa72e-6554-4b21-b2a1-d82aa71eebbf · outbound

This paper cites Formal verification of piece-wise linear feed-forward neural networks.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Formal verification of piece-wise linear feed-forward neural networks

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:20:22.212145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6a67b3f0-0759-4470-869d-400fc974abd9 · outbound

This paper cites Scalable mechanism design for multi-agent path finding.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Scalable mechanism design for multi-agent path finding

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:16.915874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff82c637-eb77-4dc8-a463-e8c0ecfea60f · outbound

This paper cites Multi-agent Path Finding with Continuous Time Viewed Through Satisfiability Modulo Theories (SMT).

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Multi-agent Path Finding with Continuous Time Viewed Through Satisfiability Modulo Theories (SMT)

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:18.615429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0964045-ac46-478c-ab61-438d5c8a7697 · outbound

This paper cites Offline Time-Independent Multi-Agent Path Planning.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Offline Time-Independent Multi-Agent Path Planning

Reference 2019

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:20:20.449584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a5ce5b98-f0c5-4eec-ac24-032c1b1d8d5f · outbound

This paper cites Anytime multi- agent path finding via large neighborhood search.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Anytime multi- agent path finding via large neighborhood search

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:20:21.635207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 76b0651f-42ae-4715-990e-e9fd5eb80e1a · outbound

This paper cites Accessed: 2024-12-03.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Accessed: 2024-12-03

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:20:22.285935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8f72e3f5-ef28-4dca-985c-ba1c71128c81 · outbound

This paper cites Why Solving Multi-agent Path Finding with Large Language Model has not Succeeded Yet.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Why Solving Multi-agent Path Finding with Large Language Model has not Succeeded Yet

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:16.605756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 951789c2-afc1-435d-bc43-18f6214094f2 · outbound

This paper cites Multi-Agent Path Finding in Continuous Spaces with Projected Diffusion Models.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Multi-Agent Path Finding in Continuous Spaces with Projected Diffusion Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T14:20:17.296657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1aa2af82-e184-4e40-92f6-d61bd00085c1 · outbound

This paper cites Mapfaster: A faster and simpler take on multi-agent path finding algorithm selection.

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding Mapfaster: A faster and simpler take on multi-agent path finding algorithm selection

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:20:22.482261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation 6a6d821e-f344-472a-9214-c2edb4757088 · inbound

Advancing MAPF Toward the Real World: A Scalable Multi-Agent Realistic Testbed (SMART) cites this paper.

Advancing MAPF Toward the Real World: A Scalable Multi-Agent Realistic Testbed (SMART) Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:05:19.514246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.