# Questions tagged [td3]

For questions related to the Twin Delayed Deep Deterministic policy gradient algorithm (TD3).

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### If we have a working reward function, would adding another action have a significant effect on the agent performance if task remains the same?

If we have a working reward function, providing the desired behavior and optimal policy in a continuous action/state-space problem, would adding another action significantly affect the possible ...
31 views

### Training a RL agent using different data at each episode

I am training a RL agent whose state is composed of two numbers, ranging between 4 ~ 16 and 0 ~ 360. The action is continuous and between 0~90. In real life, the states can be any I am training a TD3 ...
• 49
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### How to limit the action space and normalize at the same time in PPO?

In PPO (or TD3), how can you both determine the minimum and maximum action the agent can take (for example, between 0 and 1) and also make sure that all the actions sum up to 1? In Python, I can use <...
• 101
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### Is it possible to use Softmax as an activation function for actor (policy) network in TD3 or SAC Reinforcement learning algorithms?

As I understand from literature, normally, the last activation in an actor (policy) network in TD3 and SAC algorithms is a Tanh function, which is scaled by a certain limit. My action vector is ...
38 views

### RL agent policy performs worse than random policy

I am training a trading bot with TD3 and SAC algorithms. During the first 10k steps it takes uniformly random actions before running policy learnt so far. The agent starts to do gradient descent ...
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### TD3 sticking to end values [closed]

I am using TD3 on a custom gym environment, but the problem is that the action values stick to the end. Sticking to the end values makes reward negative, to be positive it must find action values ...
46 views

### Actor-critic reinforcement learning updates and episode length

I am currently using a TD3 agent-critic network to control a vehicle suspension system, where the reward (or rather a penalty) is based on the vertical acceleration of the mass and is calculated at ...