it establishes a temperature distribution model using K-means clustering and heat conduction equations, and optimizes heat dissipation parameters using the least squares method. Ultimately, it ...

A quantum-inspired Q-learning (QIQL) algorithm is proposed for indoor robot navigation control. Q- learning is an action-dependent reinforcement learning method and has been widely used in robot ...

This paper presents a novel Q-learning algorithm to address the optimal load frequency control (LFC) problem in a single-area power system with unknown parameters. LFC is a critical issue for ensuring ...

In this study, we analyze the boundaries of applying machine learning via reinforcement learning (RL) for genome assembly. We expand upon the previous approach found in the literature to solve this ...