Pith. sign in

Paper Citation Record · LEDGER

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

As of 20 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 2026-08-20T06:33:59.587034+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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:16.837612Z digest=sha256:04a5937f26cf5cf4dc2b93afda5d93c51d0149a037da7dfb0c2bc3fa6cd97eae

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:16.985547Z digest=sha256:bcd381278415cff357e7895c18ed5ba797606324604dc3aeef0319656ebd54eb

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.

source=pdf_text observed=2026-08-07T14:20:17.064529Z digest=sha256:b9251f33c8cb792d5cfa6fe875427595e01f3faf415910ba67744aec8c08c850

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.

source=pdf_text observed=2026-08-07T14:20:17.394115Z digest=sha256:bab1eb6bf88945ace5b2e9687b6e45b37149476b30ca2dd3dfd42686e31d193e

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.

source=pdf_text observed=2026-08-07T14:20:17.490938Z digest=sha256:9e9facad47823ec432e6584493c065a0054f354e67b9b417d1d1bbe1e5ac15d4

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.

source=pdf_text observed=2026-08-07T14:20:17.624351Z digest=sha256:3c3ad1e416761e4eccd0e2c90a2b7f894efeb50b29e12b9f9c0bdec6887bdf8d

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:17.723877Z digest=sha256:65affd0b861c549f07059b08c55e7e37acfac4c33eff18fab3f4a232aa2e5deb

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:17.819213Z digest=sha256:cc9eb6779a69443aae144971e8beb992cacfadf4cc5d55ee5e4a91078c5a1b05

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:18.012983Z digest=sha256:2fdeb457de009495a277e7d70dc38652e21def36df05ee34758c8d931ff9fb5f

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:18.108613Z digest=sha256:236c2a3017c04cde7d2f9a0abbaef2a304bb1ff6c3f22df7c2786513cccd0897

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:18.185373Z digest=sha256:7538033a8f7b7fe581b6fa031889f603144bed9861d378cb9c843c7cf18dfcbf

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:18.259433Z digest=sha256:117caeb11bf5cbadef8126203594bf6be43d7a62edb57c65ffa4f2cb74c0ab72

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.

source=pdf_text observed=2026-08-07T14:20:18.362271Z digest=sha256:d4da565a59c70396f4515919fda98ea926c137e295fd78560ddb23658402b068

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:18.454334Z digest=sha256:baf1bc1d65711bac556bba902b265b0739a5f17027000f95bd6b32cac156b589

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.

source=pdf_text observed=2026-08-07T14:20:18.526685Z digest=sha256:140b9993b31b5acf57921d4f76ca9217adbf8b6e5684061d66594c8691138c13

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:18.686763Z digest=sha256:c779f08f742c4cdd22de494764b632bf41ff0b9405ff772a27ed2249bddbaf38

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.

source=pdf_text observed=2026-08-07T14:20:18.775994Z digest=sha256:edf42fb7b873d78348bf903e4e5162abc11fc33918326351d67a9df3756ca498

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:18.830412Z digest=sha256:45e355c16443e9323f48ff16490468e107967d19d72b9a60e86cd27d1817abac

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:18.909676Z digest=sha256:db4787a8d0f0e2387d83db05b706147c1ea28ae2c334c3b38067e492e412068f

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.

source=pdf_text observed=2026-08-07T14:20:18.987183Z digest=sha256:765c8434079e0ee9fa8501b2dbbf397ccd50edc3b8345323b2e364908dbe4359

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:16.688404Z digest=sha256:7644ef21b7c5abb64f35ac37bf8f38845ae51e1bcc33985e8370eabd30f4fa4d

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.

source=pdf_text observed=2026-08-07T14:20:16.915874Z digest=sha256:a1048c1576954b1642db4f494063d25a200578d8b46f90379cc49e50954156ee

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.

source=pdf_text observed=2026-08-07T14:20:18.615429Z digest=sha256:d192f1360280372f509412bd136f242e05c818e89eae0c33a2ea1801f1056baf

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:17.917831Z digest=sha256:9cf3e3dffedea4ce1e3d1b14ddbb0f9875e9a614b6a781d8ab57d749e523846b

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:17.164612Z digest=sha256:f336e51a5e6cec1f7ca818407ed0f7933a1a0b1c44b7a688b4e25508c13da0cd

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:16.478315Z digest=sha256:dcca834400b215c7ba6ec56fa0c2ccb8f28d218cc2125e875aedf575f9c042ba

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.

source=pdf_text observed=2026-08-07T14:20:16.605756Z digest=sha256:03a893265295ee4083559f1895122260077af9b292089509493c328926ff70ee

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.

source=pdf_text observed=2026-08-07T14:20:17.296657Z digest=sha256:c92118a48d3392b85eca585aa238c2ecd5ba135750aceb369fc2735ed7217c69

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:20:16.416386Z digest=sha256:a97aaa0e290965b256d7a02d9172bcdf0fc4039b6caf014fd7a4618891537aef

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-23T02:03:47.244209Z digest=sha256:ede8f932a96832c0c49a71ea2e250659aa0c4418f4fe92fa1aebb05064efde5a