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Deep Reinforcement Learning for Autonomous Cyber Operations: A Survey
An overview of state-of-the-art approaches for scaling DRL to domains that confront learners with the curse of dimensionality, and; iv.)
Renewable energy integration and microgrid energy trading using multi-agent deep reinforcement learning
In this paper, multi-agent reinforcement learning is used to control a hybrid energy storage system working collaboratively to reduce the energy costs of a microgrid through maximising the value of renewable energy and trading.
Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning
As the world seeks to become more sustainable, intelligent solutions are needed to increase the penetration of renewable energy.
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