Abstract: The inherent cross-coupling phenomenon in three-input three-output active magnetic compensation (AMC) systems employing multiaxial coil configurations hinders precise system characterization ...

Abstract: In this article, a novel accelerated evolution-guided Q-learning (EGQL) algorithm is introduced to address optimal control problems for unknown nonlinear systems. A novel adaptive ...

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: Generative AI is poised to revolutionize performance engineering by automating key tasks, improving prediction accuracy, and enabling real-time system adaptation. This paper explores the ...

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 ...

Revised: This Reviewed Preprint has been revised by the authors in response to the previous round of peer review; the eLife assessment and the public reviews have been updated where necessary by the ...

Aiming at the problems of slow network convergence, poor reward convergence stability, and low path planning efficiency of traditional deep reinforcement learning algorithms, this paper proposes a ...

Integration of Reinforcement Learning RL with large language models catalyzes LLM’s performance on distinct specialty tasks such as robotics control or natural language processing that require ...