Extreme events such as earthquakes can readily cause structural damage and operational disturbances in power grids, thereby weakening the system’s supply stability and recovery capability and posing ...
Abstract: Reinforcement learning algorithms have revolutionized autonomous decision-making in various domains. In this paper, we compare Q-learning and DQN for solving a 100x100 grid model of a ...
Abstract: To address the issues of slow convergence speed and poor path planning performance in dynamic obstacle environments. This paper proposes an improved Q-Learning path planning algorithm for ...
Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms as well as supporting myriad research applications. Of particular interest ...
In this tutorial, we explore how exploration strategies shape intelligent decision-making through agent-based problem solving. We build and train three agents, Q-Learning with epsilon-greedy ...
Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I examine the importance of performing ...
Researchers at Sandia National Laboratories have developed AI algorithms to detect physical problems, cyberattacks and both at the same time within the grid. “As more disturbances occur, whether from ...
Cabin life in the rainforest begins as Aki and I fulfill our lifelong dream of living closer to nature and more sustainably. We dive into cabin life without formal construction experience, tackling ...
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