Multi-Agent Path Finding

10 papers with code • 0 benchmarks • 1 datasets

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Most implemented papers

MAPFAST: A Deep Algorithm Selector for Multi Agent Path Finding using Shortest Path Embeddings

USC-ACTLab/MAPFAST 24 Feb 2021

Solving the Multi-Agent Path Finding (MAPF) problem optimally is known to be NP-Hard for both make-span and total arrival time minimization.

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

ct2034/cobra 30 May 2017

In the MAPD problem, agents have to attend to a stream of delivery tasks in an online setting.

Lifelong Multi-Agent Path Finding in Large-Scale Warehouses

Jiaoyang-Li/RHCR 15 May 2020

Multi-Agent Path Finding (MAPF) is the problem of moving a team of agents to their goal locations without collisions.

EECBS: A Bounded-Suboptimal Search for Multi-Agent Path Finding

Jiaoyang-Li/EECBS 3 Oct 2020

ECBS is a bounded-suboptimal variant of CBS that uses focal search to speed up CBS by sacrificing optimality and instead guaranteeing that the costs of its solutions are within a given factor of optimal.

Improving Continuous-time Conflict Based Search

PathPlanning/Continuous-CBS 24 Jan 2021

Conflict-Based Search (CBS) is a powerful algorithmic framework for optimally solving classical multi-agent path finding (MAPF) problems, where time is discretized into the time steps.

Distributed Heuristic Multi-Agent Path Finding with Communication

ZiyuanMa/DHC 21 Jun 2021

The final trained policy is applied to each agent for decentralized execution.

Learning Selective Communication for Multi-Agent Path Finding

ziyuanma/dcc 12 Sep 2021

Learning communication via deep reinforcement learning (RL) or imitation learning (IL) has recently been shown to be an effective way to solve Multi-Agent Path Finding (MAPF).

Subdimensional Expansion Using Attention-Based Learning For Multi-Agent Path Finding

lakshayvirmani/learning-assisted-mstar 29 Sep 2021

By leveraging a Visual Transformer, we develop a learning-based single-agent planner, which plans for a single agent while paying attention to both the structure of the map and other agents with whom conflicts may happen.

Coordinated Multi-Agent Pathfinding for Drones and Trucks over Road Networks

shushman/aerialgroundpathfinding.jl 17 Oct 2021

The second stage solves only for drones, by routing them over a composite of the road network and the transit network defined by truck paths from the first stage.

Multi-Agent Path Finding with Prioritized Communication Learning

mail-ecnu/PICO 8 Feb 2022

The learning-based, fully decentralized framework has been introduced to alleviate real-time problems and simultaneously pursue optimal planning policy.