activity
20162024
most citedOptimal Target Assignment and Path Finding for Teams of Agents

67 citations · 104 across the 15 of their papers we have counts for

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6 papers · 1 filter

cs.AI20231 cited

Artificial Intelligence/Operations Research Workshop 2 Report Out

John Dickerson, Bistra Dilkina, Yu Ding +9

This workshop Report Out focuses on the foundational elements of trustworthy AI and OR technology, and how to ensure all AI and OR systems implement these elements in their system…

cs.AI2022

The (Un)Scalability of Heuristic Approximators for NP-Hard Search Problems

Sumedh Pendurkar, Taoan Huang, Sven Koenig +1

The A* algorithm is commonly used to solve NP-hard combinatorial optimization problems. When provided with a completely informed heuristic function, A* solves many NP-hard minimum-…

cs.AI2022

Multi-Goal Multi-Agent Pickup and Delivery

Qinghong Xu, Jiaoyang Li, Sven Koenig +1

In this work, we consider the Multi-Agent Pickup-and-Delivery (MAPD) problem, where agents constantly engage with new tasks and need to plan collision-free paths to execute them. T…

cs.AI2022

Optimal and Bounded-Suboptimal Multi-Goal Task Assignment and Path Finding

Xinyi Zhong, Jiaoyang Li, Sven Koenig +1

We formalize and study the multi-goal task assignment and path finding (MG-TAPF) problem from theoretical and algorithmic perspectives. The MG-TAPF problem is to compute an assignm…

cs.AI201667 cited

Optimal Target Assignment and Path Finding for Teams of Agents

Hang Ma, Sven Koenig

We study the TAPF (combined target-assignment and path-finding) problem for teams of agents in known terrain, which generalizes both the anonymous and non-anonymous multi-agent pat…

cs.AI201628 cited

Multi-Agent Path Finding with Delay Probabilities

Hang Ma, T. K. Satish Kumar, Sven Koenig

Several recently developed Multi-Agent Path Finding (MAPF) solvers scale to large MAPF instances by searching for MAPF plans on 2 levels: The high-level search resolves collisions…