research
∙
08/22/2023
A Semi-automatic Oriental Ink Painting Framework for Robotic Drawing from 3D Models
Creating visually pleasing stylized ink paintings from 3D models is a ch...
share
research
∙
06/05/2023
A General Perspective on Objectives of Reinforcement Learning
In this lecture, we present a general perspective on reinforcement learn...
research
∙
05/22/2023
Policy Representation via Diffusion Probability Model for Reinforcement Learning
Popular reinforcement learning (RL) algorithms tend to produce a unimoda...
research
∙
01/25/2023
Energy-Delay Tradeoff in Helper-Assisted NOMA-MEC Systems: A Four-Sided Matching Algorithm
This paper designs a helper-assisted resource allocation strategy in non...
research
∙
08/30/2022
Optimal Probabilistic Constellation Shaping for Covert Communications
In this paper, we investigate the optimal probabilistic constellation sh...
research
∙
05/24/2022
Penalized Proximal Policy Optimization for Safe Reinforcement Learning
Safe reinforcement learning aims to learn the optimal policy while satis...
research
∙
06/15/2021
Thompson Sampling for Unimodal Bandits
In this paper, we propose a Thompson Sampling algorithm for unimodal ban...
research
∙
12/02/2020
Sample Complexity of Policy Gradient Finding Second-Order Stationary Points
The goal of policy-based reinforcement learning (RL) is to search the ma...
research
∙
09/06/2019
Gradient Q(σ, λ): A Unified Algorithm with Function Approximation for Reinforcement Learning
Full-sampling (e.g., Q-learning) and pure-expectation (e.g., Expected Sa...
research
∙
07/01/2019
FiDi-RL: Incorporating Deep Reinforcement Learning with Finite-Difference Policy Search for Efficient Learning of Continuous Control
In recent years significant progress has been made in dealing with chall...
research
∙
06/25/2019
Policy Optimization with Stochastic Mirror Descent
Stochastic mirror descent (SMD) keeps the advantages of simplicity of im...
research
∙
06/25/2019
Expected Sarsa(λ) with Control Variate for Variance Reduction
Off-policy learning is powerful for reinforcement learning. However, the...
research
∙
05/17/2019
TBQ(σ): Improving Efficiency of Trace Utilization for Off-Policy Reinforcement Learning
Off-policy reinforcement learning with eligibility traces is challenging...
research
∙
08/01/2018
Beetle Swarm Optimization Algorithm:Theory and Application
In this paper, a new meta-heuristic algorithm, called beetle swarm optim...
research
∙
06/14/2018
Qualitative Measurements of Policy Discrepancy for Return-based Deep Q-Network
In this paper, we focus on policy discrepancy in return-based deep Q-net...
research
∙
02/09/2018