Questions tagged [trust-region-policy-optimization]
For questions about the Trust Region Policy Optimization (TRPO) algorithm, which was introduced in the paper "Trust Region Policy Optimization" (2015) by J. Schulman et al.
11
questions
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vote
0answers
20 views
Is (log-)standard deviation learned in TRPO and PPO or fixed instead?
After having read Williams (1992), where it was suggested that actually both the mean and standard deviation can be learned while training a REINFORCE algorithm on generating continuous output values, ...
1
vote
1answer
59 views
Why does each component of the tuple that represents an action have a categorical distribution in the TRPO paper?
I was going through the TRPO paper, and there was a line under Appendix D "Approximating Factored Policies with Neural Networks" in the last paragraph which I am unable to understand
The ...
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vote
0answers
47 views
Why does PPO lead to a worse performance than TRPO in the same task?
I am training an agent with an Actor-Critic network and update it with TRPO so far. Now, I tried out PPO and the results are drastically different and bad. I only changed from TRPO to PPO, the rest of ...
2
votes
1answer
79 views
How can I implement the reward function for an 8-DOF robot arm with TRPO?
I need to get an 8-DOF (degrees of freedom) robot arm to move a specified point. I need to implement the TRPO RL code using OpenAI gym. I already have the gazebo environment. But I am unsure of how to ...
3
votes
1answer
105 views
Understanding proof of lemma 1 (policy improvement bound) of the “Trust Region Policy Optimization” paper
In the Trust Region Policy Optimization paper, in Lemma 1 of Appendix A, I did not quite understand the transition from (21) from (20). In going from (20) to (21), $A^\pi(s_t, a_t)$ is substituted ...
3
votes
1answer
124 views
Are these two TRPO objective functions equivalent?
In the TRPO paper, the objective to maximize is (equation 14)
$$
\mathbb{E}_{s\sim\rho_{\theta_\text{old}},a\sim q}\left[\frac{\pi_\theta(a|s)}{q(a|s)} Q_{\theta_\text{old}}(s,a) \right]
$$
which ...
2
votes
0answers
52 views
How does the TRPO surrogate loss account for the error in the policy?
In the Trust Region Policy Optimization (TRPO) paper, on page 10, it is stated
An informal overview is as follows. Our proof relies on the notion of coupling, where we jointly define the ...
2
votes
1answer
138 views
Understanding lemma 2 of the “Trust Region Policy Optimization” paper
In the Trust Region Policy Optimization paper, in Lemma 2 of Appendix A, I did not quite understand deriving inequality (31) from (30), which is:
$$\bar{A}(s) = P(a \neq \tilde{a} | s) \mathbb{E}_{(a,...
6
votes
2answers
806 views
Why is the log probability replaced with the importance sampling in the loss function?
In the Trust-Region Policy Optimisation (TRPO) algorithm (and subsequently in PPO also), I do not understand the motivation behind replacing the log probability term from standard policy gradients
$$L^...
3
votes
1answer
55 views
Maximizing or Minimizing in Trust Region Policy Optimization?
I happened to discover that the v1 (19 Feb 2015) and the v5 (20 Apr 2017) versions of TRPO papers have two different conclusions. The Equation (15) in v1 is $\min_\theta$ while the Equation (14) in v2 ...
14
votes
1answer
6k views
How can policy gradients be applied in the case of multiple continuous actions?
Trusted Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO) are two cutting edge policy gradients algorithms.
When using a single continuous action, normally, you would use some ...
