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minimum change for lower bounded value target (for episodic return, goal distance return, and n-step bootstrapped return)

@le-horizon le-horizon requested review from emailweixu and hnyu May 17, 2022 16:03
return importance_ratio, importance_ratio_clipped


def generalized_advantage_estimation(rewards,
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I didn't change generalized_advantage_estimation, only moved it closer to action_importance_ratio, git messed up the diff..

@le-horizon le-horizon mentioned this pull request May 17, 2022
improve_w_goal_return: Use return calculated from the distance to hindsight
goals. Only supports batch_length == 2, one step td.
improve_w_nstep_bootstrap: Look ahead 2 to n steps, and take the largest
bootstrapped return to lower bound the value target of the 1st step.
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add formula

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Done.

Le Horizon added 2 commits June 27, 2022 10:57
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@emailweixu and @hnyu , I've separated out the HER related logic (the part that move batch_info fields into alg_info and loss calculation) into a new file her_algorithms.

Let me know how you like this version.

Thanks,
Le

improve_w_goal_return: Use return calculated from the distance to hindsight
goals. Only supports batch_length == 2, one step td.
improve_w_nstep_bootstrap: Look ahead 2 to n steps, and take the largest
bootstrapped return to lower bound the value target of the 1st step.
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Done.

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