Skip to main content
Artificial Intelligence

Return to Question

added 4 characters in body; edited tags; edited title
Source Link
nbro
nbro
  • 41.4k
  • 12
  • 115
  • 205

Computing How do I compute the value function when the reward is only at the end in the context of actor-critic algorithms?

Consider the actor-critic reinforcement learning setting (actor and critic parameterized by a neural network). The reward is given only at the end of the episode (or when there is a timeout there is no reward). How

How could we learn the value function? Do you recommend computing intermediate rewards?

Computing the value function when the reward is only at the end

Consider the actor-critic reinforcement learning setting (actor and critic parameterized by a neural network). The reward is given only at the end of the episode (or when there is timeout there is no reward). How could we learn the value function? Do you recommend computing intermediate rewards?

How do I compute the value function when the reward is only at the end in the context of actor-critic algorithms?

Consider the actor-critic reinforcement learning setting (actor and critic parameterized by a neural network). The reward is given only at the end of the episode (or when there is a timeout there is no reward).

How could we learn the value function? Do you recommend computing intermediate rewards?

Source Link
cerebrou
cerebrou
  • 161
  • 1
  • 3

Computing the value function when the reward is only at the end

Consider the actor-critic reinforcement learning setting (actor and critic parameterized by a neural network). The reward is given only at the end of the episode (or when there is timeout there is no reward). How could we learn the value function? Do you recommend computing intermediate rewards?