activity
20212026
most citedEnergy-Aware Multi-Robot Task Allocation in Persistent Tasks

4 citations · 6 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2026

ConTraIRL: Factorized Contrastive Abstractions for Transferable IRL

Yikang Gui, Bikramjit Banerjee, Prashant Doshi

Reward transfer in Inverse Reinforcement Learning (IRL) is unreliable when policies must generalize to unseen combinations of environment dynamics and task goals. We propose Factor…

cs.LG2025

Inversely Learning Transferable Rewards via Abstracted States

Yikang Gui, Prashant Doshi

Inverse reinforcement learning (IRL) has progressed significantly toward accurately learning the underlying rewards in both discrete and continuous domains from behavior data. The…

cs.LG2023

A Novel Variational Lower Bound for Inverse Reinforcement Learning

Yikang Gui, Prashant Doshi

Inverse reinforcement learning (IRL) seeks to learn the reward function from expert trajectories, to understand the task for imitation or collaboration thereby removing the need fo…

cs.LG2022★ 1 cited

IRL with Partial Observations using the Principle of Uncertain Maximum Entropy

Kenneth Bogert, Yikang Gui, Prashant Doshi

The principle of maximum entropy is a broadly applicable technique for computing a distribution with the least amount of information possible while constrained to match empirically…

cs.RO2022

Message Expiration-Based Distributed Multi-Robot Task Management

Yikang Gui, Ehsan Latif, Ramviyas Parasuraman

Distributed task assignment for multiple agents raises fundamental and novel control theory and robotics problems. A new challenge is the development of distributed algorithms that…

cs.RO2021★ 4 cited

Energy-Aware Multi-Robot Task Allocation in Persistent Tasks

Ehsan Latif, Yikang Gui, Aiman Munir +1

The applicability of the swarm robots to perform foraging tasks is inspired by their compact size and cost. A considerable amount of energy is required to perform such tasks, espec…

cs.RO2021★ 1 cited

Adaptive Agent Architecture for Real-time Human-Agent Teaming

Tianwei Ni, Huao Li, Siddharth Agrawal +6

Teamwork is a set of interrelated reasoning, actions and behaviors of team members that facilitate common objectives. Teamwork theory and experiments have resulted in a set of stat…