An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...

AI researcher Anmol Aggarwal explains how fairness-aware pricing algorithms can reduce hidden bias without major revenue loss ...

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...

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 ...

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 ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...

A high-fidelity Python implementation of the Q-learning oligopoly simulation from Calvano et al. (2020). This project provides a complete, tested, and extensible reproduction of the seminal study ...

Abstract: Q-learning and double Q-learning are well-known sample-based, off-policy reinforcement learning algorithms. However, Q-learning suffers from overestimation bias, while double Q-learning ...

Institute of Logistics Science and Engineering of Shanghai Maritime University, Pudong, China Introduction: This study addresses the joint scheduling optimization of continuous berths and quay cranes ...