Proof subtracting baseline doesn't influence gradient can be used to show no gradient exist at all?
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I am using David Silver's course in RL to help me write my thesis. However, I am baffled by the proof given in lecture 7 slide 29:
slideshow
Consider in this proof replacing $b(s)$ with the critic's quality estimate $Q_w(s,a)$ (see previous slide(s)). How does this proof not also show that the gradient of the objective function $nabla_theta J(theta)$ should also be $0$? Does this have to do with the second summation term changing from being over $a$ to over $a in mathcal{A}$?
Thank you.
reinforcement-learning policy-gradients actor-critic
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I am using David Silver's course in RL to help me write my thesis. However, I am baffled by the proof given in lecture 7 slide 29:
slideshow
Consider in this proof replacing $b(s)$ with the critic's quality estimate $Q_w(s,a)$ (see previous slide(s)). How does this proof not also show that the gradient of the objective function $nabla_theta J(theta)$ should also be $0$? Does this have to do with the second summation term changing from being over $a$ to over $a in mathcal{A}$?
Thank you.
reinforcement-learning policy-gradients actor-critic
New contributor
Alex Van de Kleut is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I am using David Silver's course in RL to help me write my thesis. However, I am baffled by the proof given in lecture 7 slide 29:
slideshow
Consider in this proof replacing $b(s)$ with the critic's quality estimate $Q_w(s,a)$ (see previous slide(s)). How does this proof not also show that the gradient of the objective function $nabla_theta J(theta)$ should also be $0$? Does this have to do with the second summation term changing from being over $a$ to over $a in mathcal{A}$?
Thank you.
reinforcement-learning policy-gradients actor-critic
New contributor
Alex Van de Kleut is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I am using David Silver's course in RL to help me write my thesis. However, I am baffled by the proof given in lecture 7 slide 29:
slideshow
Consider in this proof replacing $b(s)$ with the critic's quality estimate $Q_w(s,a)$ (see previous slide(s)). How does this proof not also show that the gradient of the objective function $nabla_theta J(theta)$ should also be $0$? Does this have to do with the second summation term changing from being over $a$ to over $a in mathcal{A}$?
Thank you.
reinforcement-learning policy-gradients actor-critic
reinforcement-learning policy-gradients actor-critic
New contributor
Alex Van de Kleut is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Alex Van de Kleut is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Alex Van de Kleut is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 6 mins ago
Alex Van de KleutAlex Van de Kleut
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