# Questions tagged [discrete-action-spaces]

For questions about discrete action spaces in the context of reinforcement learning (or other artificial intelligence sub-fields). There is also the tag for continuous action spaces.

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### How to apply DRL to solve a problem that involves mixed discrete-continuous action spaces where the action's size changes over time?

I have a reinforcement learning problem where a possible action is a probability vector $[p_1\ldots,p_n]$ of size $n\in\{1,\ldots,N\}$, where each element $p_i$ of the vector is between $0$ and $1$ ...
• 301
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### Training Issue in Solving Multi-Dimensional Multiple Knapsack Problem with Transformer Model and PPO and SAC algorithm

I'm reaching out to the brilliant minds of the AI community to seek help with a challenging issue in my project on solving the multi-dimensional multiple knapsack problem using a transformer model. As ...
1 vote
317 views

### Model-based RL algorithms for continuous state space and finite action space

At the beginning, if I have a complete model $p(s' \mid s, a)$ (an assumed true model that describes the environment well enough) and the reward function $r(s,a,s')$. How can I exploit the model and ...
• 55
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### PPO: multiple discrete actions per step, one depends on the other

I have a custom PPO implementation, and it works fine, but I need to add to it the ability to select 2 actions per turn, one different in nature from the other, one dependent on the other. Imagine ...
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### Is there a multi-agent deep reinforcement learning algorithm which is for environments with only discrete action spaces (Not hybrid)?

Is there a multi-agent deep reinforcement learning algorithm which is for environments with only discrete action spaces (Not hybrid) and have centralized training? I have been looking for algorithms, (...
• 21
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### Can a large discrete action space be represented using Gaussian distributions?

I have a large 1D action space, e.g. dim(A)=2000-10000. Can I use continuous action space where I could learn the mean and std of the Gaussian distributions that I would use to sample action from and ...
• 341
150 views

### How to implement RL model with increasing dimensions of state space and action space?

I've read in this discussion that "reinforcement learning is a way of finding the value function of a Markov Decision Process". I want to implement an RL model, whose state space and action ...
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1 vote
410 views

### What adapts an algorithm to continuous or to discrete action spaces?

Some RL algorithms can only be used for environments with continuous action spaces (e.g TD3, SAC), while others only for discrete action spaces (DQN), and some for both REINFORCE and other policy ...
• 531
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### How to implement a variable action space in Proximal Policy Optimization?

I'm coding a Proximal Policy Optimization (PPO) agent with the Tensorforce library (which is built on top of TensorFlow). The first environment was very simple. Now, I'm diving into a more complex ...
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