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Learning Intention-Aware Policies in Deep Reinforcement Learning

Neural Computation, 2023
AbstractDeep reinforcement learning (DRL) provides an agent with an optimal policy so as to maximize the cumulative rewards. The policy defined in DRL mainly depends on the state, historical memory, and policy model parameters. However, we humans usually take actions according to our own intentions, such as moving fast or slow, besides the elements ...
Zhao, Tingting   +5 more
openaire   +3 more sources

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