A review of cooperative multi-agent deep reinforcement learning
A Oroojlooy, D Hajinezhad - Applied Intelligence, 2023 - Springer
Abstract Deep Reinforcement Learning has made significant progress in multi-agent
systems in recent years. The aim of this review article is to provide an overview of recent …
systems in recent years. The aim of this review article is to provide an overview of recent …
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 …
Multi-agent pathfinding: Definitions, variants, and benchmarks
The multi-agent pathfinding problem (MAPF) is the fundamental problem of planning paths
for multiple agents, where the key constraint is that the agents will be able to follow these …
for multiple agents, where the key constraint is that the agents will be able to follow these …
Lifelong multi-agent path finding in large-scale warehouses
Abstract Multi-Agent Path Finding (MAPF) is the problem of moving a team of agents to their
goal locations without collisions. In this paper, we study the lifelong variant of MAPF, where …
goal locations without collisions. In this paper, we study the lifelong variant of MAPF, where …
Primal: Pathfinding via reinforcement and imitation multi-agent learning
Multi-agent path finding (MAPF) is an essential component of many large-scale, real-world
robot deployments, from aerial swarms to warehouse automation. However, despite the …
robot deployments, from aerial swarms to warehouse automation. However, despite the …
Integrated task assignment and path planning for capacitated multi-agent pickup and delivery
Multi-agent Pickup and Delivery (MAPD) is a challenging industrial problem where a team of
robots is tasked with transporting a set of tasks, each from an initial location and each to a …
robots is tasked with transporting a set of tasks, each from an initial location and each to a …
MAPF-LNS2: Fast repairing for multi-agent path finding via large neighborhood search
Abstract Multi-Agent Path Finding (MAPF) is the problem of planning collision-free paths for
multiple agents in a shared environment. In this paper, we propose a novel algorithm MAPF …
multiple agents in a shared environment. In this paper, we propose a novel algorithm MAPF …
Neural graph control barrier functions guided distributed collision-avoidance multi-agent control
We consider the problem of designing distributed collision-avoidance multi-agent control in
large-scale environments with potentially moving obstacles, where a large number of agents …
large-scale environments with potentially moving obstacles, where a large number of agents …
Multi-agent motion planning from signal temporal logic specifications
We tackle the challenging problem of multi-agent cooperative motion planning for complex
tasks described using signal temporal logic (STL), where robots can have nonlinear and …
tasks described using signal temporal logic (STL), where robots can have nonlinear and …
[HTML][HTML] Priority inheritance with backtracking for iterative multi-agent path finding
Abstract In the Multi-Agent Path Finding (MAPF) problem, a set of agents moving on a graph
must reach their own respective destinations without inter-agent collisions. In practical MAPF …
must reach their own respective destinations without inter-agent collisions. In practical MAPF …