A review of graph-based multi-agent pathfinding solvers: From classical to beyond classical
Multi-agent pathfinding (MAPF) is a well-studied abstract model for navigation in a multi-
robot system, where every robot finds the path to its goal position without any collision. Due …
robot system, where every robot finds the path to its goal position without any collision. Due …
Ddm: Fast near-optimal multi-robot path planning using diversified-path and optimal sub-problem solution database heuristics
We propose a novel centralized and decoupled algorithm, DDM, for solving multi-robot path
planning problems in grid graphs, targeting on-demand and automated warehouse-like …
planning problems in grid graphs, targeting on-demand and automated warehouse-like …
Algorithm selection for optimal multi-agent pathfinding
O Kaduri, E Boyarski, R Stern - Proceedings of the international …, 2020 - ojs.aaai.org
The challenge of finding an optimal solution to a multi-agent path finding (MAPF) problem
has attracted significant academic and industrial interest in recent years. While the problem …
has attracted significant academic and industrial interest in recent years. While the problem …
MAPFAST: A deep algorithm selector for multi agent path finding using shortest path embeddings
Solving the Multi-Agent Path Finding (MAPF) problem optimally is known to be NP-Hard for
both make-span and total arrival time minimization. While many algorithms have been …
both make-span and total arrival time minimization. While many algorithms have been …
Experimental evaluation of classical multi agent path finding algorithms
O Kaduri, E Boyarski, R Stern - Proceedings of the International …, 2021 - ojs.aaai.org
Modern optimal multi-agent path finding (MAPF) algorithms can scale to solve problems with
hundreds of agents. To facilitate comparison between these algorithms, a benchmark of …
hundreds of agents. To facilitate comparison between these algorithms, a benchmark of …
A Comprehensive Review on Leveraging Machine Learning for Multi-Agent Path Finding
JM Alkazzi, K Okumura - IEEE Access, 2024 - ieeexplore.ieee.org
This review paper provides an in-depth analysis of the latest advancements in applying
Machine Learning (ML) to solve the Multi-Agent Path Finding (MAPF) problem. The MAPF …
Machine Learning (ML) to solve the Multi-Agent Path Finding (MAPF) problem. The MAPF …
Betweenness centrality in multi-agent path finding
Multi-Agent Path Finding (MAPF) is a well studied problem with many existing optimal
algorithms capable of solving a wide variety of instances, each with its own strengths and …
algorithms capable of solving a wide variety of instances, each with its own strengths and …
Synthesizing priority planning formulae for multi-agent pathfinding
Prioritized planning is a popular approach to multi-agent pathfinding. It prioritizes the agents
and then repeatedly invokes a single-agent pathfinding algorithm for each agent such that it …
and then repeatedly invokes a single-agent pathfinding algorithm for each agent such that it …
Mapfaster: A faster and simpler take on multi-agent path finding algorithm selection
JM Alkazzi, A Rizk, M Salomon… - 2022 IEEE/RSJ …, 2022 - ieeexplore.ieee.org
Portfolio-based algorithm selection can help in choosing the best suited algorithm for a
given task while leveraging the complementary strengths of the candidates. Solving the Multi …
given task while leveraging the complementary strengths of the candidates. Solving the Multi …
Optimizing space utilization for more effective multi-robot path planning
We perform a systematic exploration of the principle of Space Utilization Optimization (SUO)
as a heuristic for planning better individual paths in a decoupled multi-robot path planner …
as a heuristic for planning better individual paths in a decoupled multi-robot path planner …