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Results tagged with policy-gradients
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user 26195
For questions related to reinforcement learning algorithms often referred to as "policy gradients" (or "policy gradient algorithms"), which attempt to directly optimise a parameterised policy (without first attempting to estimate value functions) using gradients of an objective function with respect to the policy's parameters.
4
votes
1
answer
996
views
Appropriate algorithm for RL problem with sparse rewards, continuous actions and significant...
I'm working on a RL problem with the following properties:
The rewards are extremely sparse i.e. all rewards are 0 except the terminal non-zero reward. Ideally I would not use any reward engineering …
- 239
3
votes
1
answer
284
views
Purpose of using actor-critic algorithms under deterministic MDP dynamics?
One of the main disadvantages of the MC Policy Gradient algorithm (REINFORCE) as described say here is the fact that it has high variance (returns, which we sample, will significantly vary from episod …
- 239