9 citations · 13 across the 11 of their papers we have counts for
11 papers
JaxRobotarium: Training and Deploying Multi-Robot Policies in 10 Minutes
Shalin Anand Jain, Jiazhen Liu, Siva Kailas +1
Multi-agent reinforcement learning (MARL) has emerged as a promising solution for learning complex and scalable coordination behaviors in multi-robot systems. However, established…
Distributed Multi-robot Source Seeking in Unknown Environments with Unknown Number of Sources
Lingpeng Chen, Siva Kailas, Srujan Deolasee +3
We introduce a novel distributed source seeking framework, DIAS, designed for multi-robot systems in scenarios where the number of sources is unknown and potentially exceeds the nu…
Evaluating and Improving Graph-based Explanation Methods for Multi-Agent Coordination
Siva Kailas, Shalin Jain, Harish Ravichandar
Graph Neural Networks (GNNs), developed by the graph learning community, have been adopted and shown to be highly effective in multi-robot and multi-agent learning. Inspired by thi…
DyPNIPP: Predicting Environment Dynamics for RL-based Robust Informative Path Planning
Srujan Deolasee, Siva Kailas, Wenhao Luo +2
Informative path planning (IPP) is an important planning paradigm for various real-world robotic applications such as environment monitoring. IPP involves planning a path that can…
OffRIPP: Offline RL-based Informative Path Planning
Srikar Babu Gadipudi, Srujan Deolasee, Siva Kailas +3
Informative path planning (IPP) is a crucial task in robotics, where agents must design paths to gather valuable information about a target environment while adhering to resource c…
A Comparison of Imitation Learning Algorithms for Bimanual Manipulation
Michael Drolet, Simon Stepputtis, Siva Kailas +4
Amidst the wide popularity of imitation learning algorithms in robotics, their properties regarding hyperparameter sensitivity, ease of training, data efficiency, and performance h…
WIT-UAS: A Wildland-fire Infrared Thermal Dataset to Detect Crew Assets From Aerial Views
Andrew Jong, Mukai Yu, Devansh Dhrafani +4
We present the Wildland-fire Infrared Thermal (WIT-UAS) dataset for long-wave infrared sensing of crew and vehicle assets amidst prescribed wildland fire environments. While such a…
On the Role of Emergent Communication for Social Learning in Multi-Agent Reinforcement Learning
Seth Karten, Siva Kailas, Huao Li +1
Explicit communication among humans is key to coordinating and learning. Social learning, which uses cues from experts, can greatly benefit from the usage of explicit communication…
Towards True Lossless Sparse Communication in Multi-Agent Systems
Seth Karten, Mycal Tucker, Siva Kailas +1
Communication enables agents to cooperate to achieve their goals. Learning when to communicate, i.e., sparse (in time) communication, and whom to message is particularly important…
Interpretable Learned Emergent Communication for Human-Agent Teams
Seth Karten, Mycal Tucker, Huao Li +3
Learning interpretable communication is essential for multi-agent and human-agent teams (HATs). In multi-agent reinforcement learning for partially-observable environments, agents…
Multiagent Rollout and Policy Iteration for POMDP with Application to Multi-Robot Repair Problems
Sushmita Bhattacharya, Siva Kailas, Sahil Badyal +2
In this paper we consider infinite horizon discounted dynamic programming problems with finite state and control spaces, partial state observations, and a multiagent structure. We…