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näkemys - Projected Bellman Operator
Parameterized Projected Bellman Operator: A Novel Approach in Reinforcement Learning
Lernen Sie den neuartigen Ansatz des parameterisierten projizierten Bellman-Operators kennen.
Parameterized Projected Bellman Operator: A Novel Approach in Reinforcement Learning
Proposing a novel approach, the Projected Bellman Operator (PBO), learns an approximate version of the Bellman operator to improve efficiency in reinforcement learning.
Parameterized Projected Bellman Operator: A Novel Approach in Reinforcement Learning
Proposing a novel approach, the Parameterized Projected Bellman Operator (PBO), to address inefficiencies in reinforcement learning algorithms.
Parameterized Projected Bellman Operator: A Novel Approach to Reinforcement Learning
The authors introduce a novel approach, the Projected Bellman Operator (PBO), to address inefficiencies in reinforcement learning algorithms. By directly computing updated parameters of the value function, PBO eliminates the need for computationally intensive projection steps.
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