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Hang Ma

McGill University;University of Southern California;Simon Fraser University

4 papers hereh-index 314.5k citations88 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AI4
affiliations
  • McGill University;University of Southern California;Simon Fraser University
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identity via Semantic Scholar / OpenAlex

most citedOverview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios

91 citations · 233 across the 4 of their papers we have counts for

collaborators

4 papers

cs.AI2017★ 34 cited

AI Buzzwords Explained: Multi-Agent Path Finding (MAPF)

Hang Ma, Sven Koenig

Explanation of the hot topic "multi-agent path finding".

cs.AI2017★ 34 cited

Feasibility Study: Moving Non-Homogeneous Teams in Congested Video Game Environments

Hang Ma, Jingxing Yang, Liron Cohen +2

Multi-agent path finding (MAPF) is a well-studied problem in artificial intelligence, where one needs to find collision-free paths for agents with given start and goal locations. I…

cs.AI2017★ 74 cited

Lifelong Multi-Agent Path Finding for Online Pickup and Delivery Tasks

Hang Ma, Jiaoyang Li, T. K. Satish Kumar +1

The multi-agent path-finding (MAPF) problem has recently received a lot of attention. However, it does not capture important characteristics of many real-world domains, such as aut…

cs.AI2017★ 91 cited

Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios

Hang Ma, Sven Koenig, Nora Ayanian +7

Multi-agent path finding (MAPF) is well-studied in artificial intelligence, robotics, theoretical computer science and operations research. We discuss issues that arise when genera…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.