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.

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Very high dimensional optimization with large budget, requiring high quality solutions

What would be theoretically the best performing optimization algorithm(s) in this case? Very high dimensional problem: 250-500 parameters Goal is to obtain very high quality solutions, not just "...
1 vote
1 answer
96 views

What makes TRPO an actor-critic method? Where is the critic?

From what I understand, Trust Region Policy Optimization (TRPO) is a modification on Natural Policy Gradient (NPG) that derives the optimal step size $\beta$ from a KL constraint between the new and ...
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25 views

Can TRPO use replay buffers?

I understand that TRPO is a on-policy RL method and that it optimizes an expectation of the advantage or accumulated returns function over actions taken according to policy $\pi$. Is it possible to ...
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49 views

CS 285 Prof Sergey Levine Lecture, Bounding Derivation for Reinforcement Learning (TRPO)

How can we derive the final result? I can understand the first line, but don't know how the absolute term in the summation is replaced with $2\epsilon t$. https://www.youtube.com/watch?v=LtAt5M_a0dI&...
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62 views

Is the interpretation of the "batch size" in policy gradient algorithms the number of trajectories sampled in VPG and TRPO?

I would like to shore up my interpretation of the concept of "batch size". It is my understanding that in Vanilla Policy Gradients and TRPO, the "batch size" is the number of ...
0 votes
0 answers
42 views

Can you apply TRPO to a problem involving a continuous state space and justify it theoretically?

I am currently reading and trying to understand the theory behind TRPO, i.e. sections 2 and 3 from the paper here. Ultimately, I want to apply PPO to do a (single) stock trading task using the FinRL ...
1 vote
1 answer
197 views

Does importance sampling really improve sampling efficiency of TRPO or PPO?

Vanilla policy gradient has a loss function: $$\mathcal{L}_{\pi_{\theta}(\theta)} = E_{\tau \sim \pi_{\theta}}[\sum\limits_{t = 0}^{\infty}\gamma^{t}r_{t}]$$ while in TRPO it is: $$\mathcal{L}_{\pi_{\...
4 votes
1 answer
284 views

What is the difference between an on-policy distribution and state visitation frequency?

On-policy distribution is defined as follows in Sutton and Barto: On the other hand, state visitation frequency is defined as follows in Trust Region Policy Optimization: $$\rho_{\pi}(s) = \sum_{t=0}^...
3 votes
1 answer
616 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, ...
  • 755
1 vote
1 answer
73 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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1 vote
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323 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 ...
  • 31
2 votes
1 answer
270 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
1 answer
203 views

In lemma 1 of the TRPO paper, why isn't the expectation over $s'∼P(s'|s,a)$?

In the Trust Region Policy Optimization paper, in Lemma 1 of Appendix A, I didn't quite understand the transition from (21) from (20). In going from (20) to (21), $A^\pi(s_t, a_t)$ is substituted with ...
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3 votes
1 answer
181 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 ...
  • 31
2 votes
0 answers
112 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
1 answer
192 views

How is inequality 31 derived from equality 30 in lemma 2 of the "Trust Region Policy Optimization" paper?

In the Trust Region Policy Optimization paper, in Lemma 2 of Appendix A (p. 11), I didn't quite understand how inequality (31) is derived from equality (30), which is: $$\bar{A}(s) = P(a \neq \tilde{a}...
7 votes
2 answers
1k 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^...
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3 votes
1 answer
75 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 ...
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17 votes
1 answer
8k 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 ...