Tag: deep reinforcement learning

A double deep Q-network combining news and social-media sentiment with price, volume and momentum signals outperformed four machine-learning approaches in ...

An offline simulation using 12.53 million KuaiRec interactions found that a DQN recommender generated longer simulated sessions and more diverse ...

Researchers in China have developed an improved deep reinforcement learning framework that jointly optimizes trajectory prediction and lane-changing decisions, achieving ...

A new DDPG-based scheduling framework called SPARCD uses vehicle position prediction, action masking, and state filling to cut task interruption ...

A deep reinforcement learning framework that treats dynamic grid strength as an actively managed constraint cut annual wind curtailment from ...

Researchers have developed a hierarchical evolutionary deep reinforcement learning algorithm that optimizes influence spreading on multilayer hypergraphs, where group interactions ...

A new framework combining deep reinforcement learning, graph neural networks, and blockchain-based verification synchronizes distributed accounting ledgers in real time ...

A deep reinforcement learning framework with a novel dynamic attention mechanism outperforms traditional methods on static and dynamic container relocation ...

A deep reinforcement learning method called P2TO extends task offloading from edge and cloud servers down to individual virtual machines, ...

A new deep reinforcement learning framework improves personalized e-commerce marketing by balancing short-term conversions with long-term customer value.