A U.S. Naval Research Laboratory (NRL) research team successfully conducted the first reinforcement learning (RL) control of ...

Reinforcement learning focuses on rewarding desired AI actions and punishing undesired ones. Common RL algorithms include State-action-reward-state-action, Q-learning, and Deep-Q networks. RL adapts ...

The breakthrough of RhymeRL stems from an in-depth analysis of the Rollout phase in the reinforcement learning process. The research found that there is a significant “historical similarity” in the ...

This similarity primarily arises from mainstream RL algorithms such as PPO/GRPO, which use gradient clipping mechanisms to ensure training stability. This mechanism smooths the model's evolutionary ...

Pairing artificial intelligence techniques called Q-learning and advantage actor-critic provides new way to optimize hybrid photovoltaic-thermoelectric systems.

The bird has never gotten much credit for being intelligent. But the reinforcement learning powering the world’s most ...

Reinforcement learning is one of the exciting branches of artificial intelligence. It plays an important role in game-playing AI systems, modern robots, chip-design systems, and other applications.

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