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38 votes
Accepted

What is the credit assignment problem?

In reinforcement learning (RL), an agent interacts with an environment in time steps. On each time step, the agent takes an action in a certain state and the environment emits a percept or perception, ...
nbro's user avatar
  • 40.9k
13 votes
Accepted

Can reinforcement learning be used for tasks where only one final reward is received?

RL can be used for cases where you have sparse rewards (i.e. at almost every step all rewards are zero), but, in such a setting, the experience the agent receives during the trajectory does not ...
nbro's user avatar
  • 40.9k
3 votes

How are "lags" and "exogenous factors" accounted for in reinforcement learning?

One of Reinforcement Learning's core features is the ability to deal with delayed rewards/punishments - i.e. rewards that may occur as a consequence of a decision that occurred multiple time steps ago....
Neil Slater's user avatar
  • 32.7k

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