Abstract: The increasing calls for the participation of prosumers and Distributed Energy Resources (DERs) have led to a three-fold shift in the operation of distribution networks, i.e., the evolution ...
Motivated by "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem" by Jiang et. al. 2017 [1]. In this project: Implement three state-of-art continous deep ...
Understanding the differences between probabilistic and deterministic AI will help manufacturers make more informed choices and achieve measurable results. As professionals become interested in using ...
1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price. Unhappy with their meager profits, they meet one night in a ...
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 ...
Aiming to address the complexity and uncertainty of unmanned aerial vehicle (UAV) aerial confrontation, a twin delayed deep deterministic policy gradient (TD3)–long short-term memory (LSTM) ...
Public sector organizations are under relentless pressure to modernize and digitize. With citizens demanding better services and governments facing ever-evolving cyber threats, deploying public ...
LinkedIn's algorithm prioritizes ads & sponsored content, hurting organic reach for creators. To adapt: share niche expertise, use authentic images, craft strong hooks, write longer comments, engage ...
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