activity
20102023
most citedPRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning

425 citations · 982 across the 23 of their papers we have counts for

collaborators
Showing 2018Show all

7 papers · 1 filter

cs.AI2018★ 2 cited

Searching with Consistent Prioritization for Multi-Agent Path Finding

Hang Ma, Daniel Harabor, Peter J. Stuckey +2

We study prioritized planning for Multi-Agent Path Finding (MAPF). Existing prioritized MAPF algorithms depend on rule-of-thumb heuristics and random assignment to determine a fixe…

cs.AI2018★ 18 cited

Lifelong Path Planning with Kinematic Constraints for Multi-Agent Pickup and Delivery

Hang Ma, Wolfgang Hönig, T. K. Satish Kumar +2

The Multi-Agent Pickup and Delivery (MAPD) problem models applications where a large number of agents attend to a stream of incoming pickup-and-delivery tasks. Token Passing (TP) i…

math.NA2018★ 3 cited

Adaptive Uzawa algorithm for the Stokes equation

Giovanni Di Fratta, Thomas Führer, Gregor Gantner +1

Based on the Uzawa algorithm, we consider an adaptive finite element method for the Stokes system. We prove linear convergence with optimal algebraic rates for the residual estimat…

cs.RO2018★ 425 cited

PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning

Guillaume Sartoretti, Justin Kerr, Yunfei Shi +4

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 commun…

cs.AI2018★ 2 cited

Multi-Agent Path Finding with Deadlines

Hang Ma, Glenn Wagner, Ariel Felner +3

We formalize Multi-Agent Path Finding with Deadlines (MAPF-DL). The objective is to maximize the number of agents that can reach their given goal vertices from their given start ve…

cs.AI2018★ 6 cited

Multi-Agent Path Finding with Deadlines: Preliminary Results

Hang Ma, Glenn Wagner, Ariel Felner +3

We formalize the problem of multi-agent path finding with deadlines (MAPF-DL). The objective is to maximize the number of agents that can reach their given goal vertices from their…