6 citations · 15 across the 12 of their papers we have counts for
4 papers · 1 filter
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…
Interpretable Model-based Hierarchical Reinforcement Learning using Inductive Logic Programming
Duo Xu, Faramarz Fekri
Recently deep reinforcement learning has achieved tremendous success in wide ranges of applications. However, it notoriously lacks data-efficiency and interpretability. Data-effici…
Improving Actor-Critic Reinforcement Learning via Hamiltonian Monte Carlo Method
Duo Xu, Faramarz Fekri
The actor-critic RL is widely used in various robotic control tasks. By viewing the actor-critic RL from the perspective of variational inference (VI), the policy network is traine…
Learning Nonlinear State Space Models with Hamiltonian Sequential Monte Carlo Sampler
Duo Xu
State space models (SSM) have been widely applied for the analysis and visualization of large sequential datasets. Sequential Monte Carlo (SMC) is a very popular particle-based met…