Mapf-gpt: Imitation learning for multi-agent pathfinding at scale
Multi-agent pathfinding (MAPF) is a challenging computational problem that typically
requires to find collision-free paths for multiple agents in a shared environment. Solving …
requires to find collision-free paths for multiple agents in a shared environment. Solving …
Safe and reconfigurable manufacturing: safety aware multi-agent control for Plug & Produce system
Plug & Produce aims to revolutionize manufacturing by enabling seamless machine
integration into production processes without extensive programming. This concept …
integration into production processes without extensive programming. This concept …
Anytime Multi-Agent Path Finding with an Adaptive Delay-Based Heuristic
Anytime multi-agent path finding (MAPF) is a promising approach to scalable path
optimization in multi-agent systems. MAPF-LNS, based on Large Neighborhood Search …
optimization in multi-agent systems. MAPF-LNS, based on Large Neighborhood Search …
Confidence-Based Curricula for Multi-Agent Path Finding via Reinforcement Learning
A wide range of real-world applications can be formulated as Multi-Agent Path Finding
(MAPF) problem, where the goal is to find collision-free paths for multiple agents with …
(MAPF) problem, where the goal is to find collision-free paths for multiple agents with …
Multi-Robot Reliable Navigation in Uncertain Topological Environments with Graph Attention Networks
This paper studies the multi-robot reliable navigation problem in uncertain topological
networks, which aims at maximizing the robot team's on-time arrival probabilities in the face …
networks, which aims at maximizing the robot team's on-time arrival probabilities in the face …