IEEE

Model-Free Q-Learning for Output Feedback Nash Strategy of Decentralized Nonzero-Sum Games

Abstract: In this article, we present a model-free output feedback (OPFB) Q-learning algorithm to find the optimal Nash equilibrium strategy for the decentralized control problem (DCP) of nonzero-sum ...
IEEE

Optimizing Successive Over-relaxation Q-learning with Deterministic Perturbation Gradient Search

Abstract: Successive Over-Relaxation Q-learning (SOR-QL) has been proposed recently as an alternative to the widely popular Q-learning algorithm as it is seen to provide better performance where ...
Frontiers

A novel reinforcement learning framework-based path planning algorithm for unmanned surface vehicle

Unmanned surface vehicles (USVs) nowadays have been widely used in ocean observation missions, helping researchers to monitor climate change, collect environmental data, and observe marine ecosystem ...
eLife

Q-learning with temporal memory to navigate turbulence

This important study uses reinforcement learning to study how turbulent odor stimuli should be processed to yield successful navigation. The authors find that there is an optimal memory length over ...
Frontiers

Reinforcement learning based estimation of shortest paths in dynamically changing transportation networks

Finding the shortest path in a network is a classical problem, and a variety of search strategies have been proposed to solve it. In this paper, we review traditional approaches for finding shortest ...