Adaptive Optimal Surrounding Control of Multiple Unmanned Surface Vessels via Actor-Critic Reinforcement Learning
R Lu, X Wang, Y Ding, HT Zhang… - … on Neural Networks …, 2024 - ieeexplore.ieee.org
In this article, an optimal surrounding control algorithm is proposed for multiple unmanned
surface vessels (USVs), in which actor-critic reinforcement learning (RL) is utilized to …
surface vessels (USVs), in which actor-critic reinforcement learning (RL) is utilized to …
Reinforcement learning for solving colored traveling salesman problems: An entropy-insensitive attention approach
T Zhu, X Shi, X Xu, J Cao - IEEE Transactions on Artificial …, 2024 - ieeexplore.ieee.org
The utilization of neural network models for solving combinatorial optimization problems
(COPs) has gained significant attention in recent years and has demonstrated encouraging …
(COPs) has gained significant attention in recent years and has demonstrated encouraging …
A Policy Resonance Approach to Solve the Problem of Responsibility Diffusion in Multiagent Reinforcement Learning
Q Fu, T Qiu, J Yi, Z Pu, X Ai… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
State-of-the-art (SOTA) multiagent reinforcement algorithms distinguish themselves in many
ways from their single-agent equivalences. However, most of them still totally inherit the …
ways from their single-agent equivalences. However, most of them still totally inherit the …
Policy consensus-based distributed deterministic multi-agent reinforcement learning over directed graphs
Learning efficient coordination policies over continuous state and action spaces remains a
huge challenge for existing distributed multi-agent reinforcement learning (MARL) …
huge challenge for existing distributed multi-agent reinforcement learning (MARL) …
Graph-based decentralized task allocation for multi-robot target localization
We introduce a new graph neural operator-based approach for task allocation in a system of
heterogeneous robots composed of Unmanned Ground Vehicles (UGVs) and Unmanned …
heterogeneous robots composed of Unmanned Ground Vehicles (UGVs) and Unmanned …
Risk-sensitive soft actor-critic for robust deep reinforcement learning under distribution shifts
We study the robustness of deep reinforcement learning algorithms against distribution shifts
within contextual multi-stage stochastic combinatorial optimization problems from the …
within contextual multi-stage stochastic combinatorial optimization problems from the …
PF-MAAC: A learning-based method for probabilistic optimization in time-constrained non-adversarial moving target search
This paper investigates the multi-robot efficient search (MuRES) problem with a focus on
maximizing the probability of capturing a moving target within a predefined time constraint …
maximizing the probability of capturing a moving target within a predefined time constraint …
Distributed entropy-regularized multi-agent reinforcement learning with policy consensus
Sample efficiency is a limiting factor for existing distributed multi-agent reinforcement
learning (MARL) algorithms over networked multi-agent systems. In this paper, the sample …
learning (MARL) algorithms over networked multi-agent systems. In this paper, the sample …
[HTML][HTML] A guided twin delayed deep deterministic reinforcement learning for vaccine allocation in human contact networks
This manuscript introduces an innovative approach to optimizing the distribution of a limited
vaccine resource within a population modeled as a contact network, aiming to mitigate the …
vaccine resource within a population modeled as a contact network, aiming to mitigate the …
Long-short-view aware multi-agent reinforcement learning for signal snippet distillation in delirium movement detection
Q Pan, H Wang, J Lou, Y Zhang, B Ji, S Li - Information Sciences, 2024 - Elsevier
Automatic movement analysis utilizing surveillance video is believed to be an important and
convenient way for timely delirium detection in an Intensive Care Unit (ICU). However, video …
convenient way for timely delirium detection in an Intensive Care Unit (ICU). However, video …