6 citations · 15 across the 12 of their papers we have counts for
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cs.LG2024
Learning Hidden Subgoals under Temporal Ordering Constraints in Reinforcement Learning
Duo Xu, Faramarz Fekri
In real-world applications, the success of completing a task is often determined by multiple key steps which are distant in time steps and have to be achieved in a fixed time order…
cs.AI2024
Generalization of Compositional Tasks with Logical Specification via Implicit Planning
Duo Xu, Faramarz Fekri
In this study, we address the challenge of learning generalizable policies for compositional tasks defined by logical specifications. These tasks consist of multiple temporally ext…
cs.AI2024
LLM-Augmented Symbolic Reinforcement Learning with Landmark-Based Task Decomposition
Alireza Kheirandish, Duo Xu, Faramarz Fekri
One of the fundamental challenges in reinforcement learning (RL) is to take a complex task and be able to decompose it to subtasks that are simpler for the RL agent to learn. In th…