As the joke goes, CRQC has been 10 to 20 years away for the past three decades. While the recent research suggests that ...
Overview: Today's high-performance cloud simulators surpass previous limits in handling qubits and accurately replicate ...
In a recent study published in Nature Communications, researchers created a memristor that uses a built-in oxygen gradient to produce slow, stable conductance changes, enabling a reinforcement ...
In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
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 ...
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 ...
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 ...
Abstract: In this paper, a new data-based Q-learning algorithm is proposed to address the optimal control issue for a class of discrete-time switched affine systems (SASs). The algorithm shifts the ...
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