86 citations · 251 across the 40 of their papers we have counts for
5 papers · 1 filter
A-MHA*: Anytime Multi-Heuristic A*
Ramkumar Natarajan, Muhammad Suhail Saleem, William Xiao +3
Designing good heuristic functions for graph search requires adequate domain knowledge. It is often easy to design heuristics that perform well and correlate with the underlying tr…
A-ePA*SE: Anytime Edge-Based Parallel A* for Slow Evaluations
Hanlan Yang, Shohin Mukherjee, Maxim Likhachev
Anytime search algorithms are useful for planning problems where a solution is desired under a limited time budget. Anytime algorithms first aim to provide a feasible solution quic…
Non-Blocking Batch A* (Technical Report)
Rishi Veerapaneni, Maxim Likhachev
Heuristic search has traditionally relied on hand-crafted or programmatically derived heuristics. Neural networks (NNs) are newer powerful tools which can be used to learn complex…
Effective Integration of Weighted Cost-to-go and Conflict Heuristic within Suboptimal CBS
Rishi Veerapaneni, Tushar Kusnur, Maxim Likhachev
Conflict-Based Search (CBS) is a popular multi-agent path finding (MAPF) solver that employs a low-level single agent planner and a high-level constraint tree to resolve conflicts.…
Enhanced Multi-Objective A* Using Balanced Binary Search Trees
Zhongqiang Ren, Richard Zhan, Sivakumar Rathinam +2
This work addresses a Multi-Objective Shortest Path Problem (MO-SPP) on a graph where the goal is to find a set of Pareto-optimal solutions from a start node to a destination in th…