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Multi-Agent Path Finding

Papers

Showing 5175 of 140 papers

TitleStatusHype
Anytime Multi-Agent Path Finding with an Adaptive Delay-Based HeuristicCode0
Algorithm Selection for Optimal Multi-Agent Path Finding via Graph Embedding0
MGCBS: An Optimal and Efficient Algorithm for Solving Multi-Goal Multi-Agent Path Finding ProblemCode0
Accelerating Search-Based Planning for Multi-Robot Manipulation by Leveraging Online-Generated Experiences0
Improving Learnt Local MAPF Policies with Heuristic Search0
A Real-Time Rescheduling Algorithm for Multi-robot Plan ExecutionCode0
Caching-Augmented Lifelong Multi-Agent Path FindingCode0
Routing and Scheduling in Answer Set Programming applied to Multi-Agent Path Finding: Preliminary Report0
A Conflict-Aware Optimal Goal Assignment Algorithm for Multi-Robot Systems0
Optimal Task Assignment and Path Planning using Conflict-Based Search with Precedence and Temporal Constraints0
Scalable Mechanism Design for Multi-Agent Path FindingCode0
Why Solving Multi-agent Path Finding with Large Language Model has not Succeeded Yet0
Bidirectional Temporal Plan Graph: Enabling Switchable Passing Orders for More Efficient Multi-Agent Path Finding Plan Execution0
Improved Anonymous Multi-Agent Path Finding Algorithm0
Optimizing Crowd-Aware Multi-Agent Path Finding through Local Communication with Graph Neural Networks0
Selective Communication for Cooperative Perception in End-to-End Autonomous Driving0
Fine-Grained Complexity Analysis of Multi-Agent Path Finding on 2D Grids0
On Computing Universal Plans for Partially Observable Multi-Agent Path Finding0
Tracking Progress in Multi-Agent Path Finding0
Double-Deck Multi-Agent Pickup and Delivery: Multi-Robot Rearrangement in Large-Scale Warehouses0
The Study of Highway for Lifelong Multi-Agent Path Finding0
Robust Multi-Agent Pickup and Delivery with Delays0
Accelerating Multi-Agent Planning Using Graph Transformers with Bounded Suboptimality0
Counterexample Guided Abstraction Refinement with Non-Refined Abstractions for Multi-Agent Path Finding0
An Efficient Approach to the Online Multi-Agent Path Finding Problem by Using Sustainable Information0
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