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 ...

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

First, let's discuss the core elements of this development, with algorithms being the most critical. In AI agent development, we often mention the use of machine learning algorithms, and of course, ...

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.

The RL model delivers almost the same cost and efficiency outcomes as the MILP optimizer, but with dramatically lower ...

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