1 citations · 2 across the 9 of their papers we have counts for
9 papers
GOMAA-Geo: GOal Modality Agnostic Active Geo-localization
Anindya Sarkar, Srikumar Sastry, Aleksis Pirinen +3
We consider the task of active geo-localization (AGL) in which an agent uses a sequence of visual cues observed during aerial navigation to find a target specified through multiple…
Learning Interpretable Policies in Hindsight-Observable POMDPs through Partially Supervised Reinforcement Learning
Michael Lanier, Ying Xu, Nathan Jacobs +2
Deep reinforcement learning has demonstrated remarkable achievements across diverse domains such as video games, robotic control, autonomous driving, and drug discovery. Common met…
Unsupervised Behavior Extraction via Random Intent Priors
Hao Hu, Yiqin Yang, Jianing Ye +2
Reward-free data is abundant and contains rich prior knowledge of human behaviors, but it is not well exploited by offline reinforcement learning (RL) algorithms. In this paper, we…
Never Explore Repeatedly in Multi-Agent Reinforcement Learning
Chenghao Li, Tonghan Wang, Chongjie Zhang +1
In the realm of multi-agent reinforcement learning, intrinsic motivations have emerged as a pivotal tool for exploration. While the computation of many intrinsic rewards relies on…
IOB: Integrating Optimization Transfer and Behavior Transfer for Multi-Policy Reuse
Siyuan Li, Hao Li, Jin Zhang +3
Humans have the ability to reuse previously learned policies to solve new tasks quickly, and reinforcement learning (RL) agents can do the same by transferring knowledge from sourc…
What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL?
Rui Yang, Yong Lin, Xiaoteng Ma +3
Offline goal-conditioned RL (GCRL) offers a way to train general-purpose agents from fully offline datasets. In addition to being conservative within the dataset, the generalizatio…