activity
20192026
most citedEntity Abstraction in Visual Model-Based Reinforcement Learning

32 citations · 72 across the 24 of their papers we have counts for

collaborators
Showing 2025Show all

6 papers · 1 filter

cs.MA2025

Conflict-Based Search as a Protocol: A Multi-Agent Motion Planning Protocol for Heterogeneous Agents, Solvers, and Independent Tasks

Rishi Veerapaneni, Alvin Tang, Haodong He +9

Imagine the future construction site, hospital, or office with dozens of robots bought from different manufacturers. How can we enable these different robots to effectively move in…

cs.MA2025

Dynamic Agent Grouping ECBS: Scaling Windowed Multi-Agent Path Finding with Completeness Guarantees

Tiannan Zhang, Rishi Veerapaneni, Shao-Hung Chan +2

Multi-Agent Path Finding (MAPF) is the problem of finding a set of collision-free paths for a team of agents. Although several MAPF methods which solve full-horizon MAPF have compl…

cs.MA2025

BTPG-max: Achieving Local Maximal Bidirectional Pairs for Bidirectional Temporal Plan Graphs

Yifan Su, Rishi Veerapaneni, Jiaoyang Li

Multi-Agent Path Finding (MAPF) requires computing collision-free paths for multiple agents in shared environment. Most MAPF planners assume that each agent reaches a specific loca…

cs.RO2025

Lazy Heuristic Search for Solving POMDPs with Expensive-to-Compute Belief Transitions

Muhammad Suhail Saleem, Rishi Veerapaneni, Maxim Likhachev

Heuristic search solvers like RTDP-Bel and LAO* have proven effective for computing optimal and bounded sub-optimal solutions for Partially Observable Markov Decision Processes (PO…

cs.AI2025

Anytime Single-Step MAPF Planning with Anytime PIBT

Nayesha Gandotra, Rishi Veerapaneni, Muhammad Suhail Saleem +3

PIBT is a popular Multi-Agent Path Finding (MAPF) method at the core of many state-of-the-art MAPF methods including LaCAM, CS-PIBT, and WPPL. The main utility of PIBT is that it i…

cs.MA2025★ 1 cited

Real-Time LaCAM for Real-Time MAPF

Runzhe Liang, Rishi Veerapaneni, Daniel Harabor +2

The vast majority of Multi-Agent Path Finding (MAPF) methods with completeness guarantees require planning full-horizon paths. However, planning full-horizon paths can take too lon…