reinforcement learning with attention
Reinforcement learning with attention refers to a framework where an agent learns to make decisions by selectively focusing on relevant information in a given context while considering long-term rewards. It combines the concept of attention, which allows the agent to dynamically allocate its focus, with reinforcement learning, which enables it to learn optimal actions through trial and error interactions with the environment.
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