mlsanityData to 7 Oct 2026

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

arXiv 1710.01447 ↗First posted 4 Oct 2017cs.AI cs.MA cs.ROcited by 21

Not on the map. Why?

Abstract (arXiv)

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. In video games, agents of different types often form teams. In this paper, we demonstrate the usefulness of MAPF algorithms from artificial intelligence for moving such non-homogeneous teams in congested video game environments.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Oct 2017.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 1; 2023: 4; 2024: 8; 2025: 5; 2026: 1.

21 papers.

Sort:

By area:

  1. 2021Distributed Heuristic Multi-Agent Path Finding with Communicationcited by 31
  2. 2024Guidance Graph Optimization for Lifelong Multi-Agent Path Findingcited by 12
  3. 2022Graph-Based Multi-Robot Path Finding and Planningcited by 7
  4. 2024Ensembling Prioritized Hybrid Policies for Multi-agent Pathfindingcited by 7
  5. 2025Advancing MAPF Toward the Real World: A Scalable Multi-Agent Realistic Testbed (SMART)cited by 5
  6. 2023Exact Algorithms and Lowerbounds for Multiagent Pathfinding: Power of Treelike Topologycited by 4
  7. 2024HiMAP: Learning Heuristics-Informed Policies for Large-Scale Multi-Agent Pathfindingcited by 4
  8. 2024MGCBS: An Optimal and Efficient Algorithm for Solving Multi-Goal Multi-Agent Path Finding Problemcited by 3
  9. 2021A Competitive Analysis of Online Multi-Agent Path Findingcited by 2
  10. 2023The Study of Highway for Lifelong Multi-Agent Path Findingcited by 2
  11. 2024Optimal and Bounded Suboptimal Any-Angle Multi-agent Pathfindingcited by 2
  12. 2023Robust Multi-Agent Pickup and Delivery with Delayscited by 1
9 more
  1. 2024QD-MAPPER: A Quality Diversity Framework to Automatically Evaluate Multi-Agent Path Finding Algorithms in Diverse Mapscited by 1
  2. 2025LLMDR: LLM-Driven Deadlock Detection and Resolution in Multi-Agent Pathfindingcited by 1
  3. 2025WinkTPG: An Execution Framework for Multi-Agent Path Finding Using Temporal Reasoningcited by 1
  4. 2026Optimization of Edge Directions and Weights for Mixed Guidance Graphs in Lifelong Multi-Agent Path Findingcited by 1
  5. 2023An Efficient Approach to the Online Multi-Agent Path Finding Problem by Using Sustainable Informationcited by 0
  6. 2024Algorithm Selection for Optimal Multi-Agent Path Finding via Graph Embeddingcited by 0
  7. 2024MFC-EQ: Mean-Field Control with Envelope Q-Learning for Moving Decentralized Agents in Formationcited by 0
  8. 2025Enhancing Lifelong Multi-Agent Path-finding by Using Artificial Potential Fieldscited by 0
  9. 2025Analyzing Planner Design Trade-offs for MAPF under ADG-based Realistic Executioncited by 0