Questions tagged [gym]
For questions about OpenAI's gym library, which provides a set of APIs to access different types of environments to train reinforcement learning agents.
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questions with no upvoted or accepted answers
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Unable to train Coach for Banana-v0 Gym environment
I have just started playing with Reinforcement learning and starting from the basics I'm trying to figure out how to solve Banana Gym with coach.
Essentially ...
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How to deal with a moving target in the Lunar Lander environment with DDPG?
I have noticed that DDPG does rather well at solving environments with a static target.
For example, the default of Lunar Lander, the flags do not change position. So the DDPG model learns how to get ...
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How does PPO with advantage normalization learn in MountainCar-v0 before first reaching the goal state?
I'm trying to figure out how PPO ever learns anything in a sparse environment like gymnasium's MountainCar-v0 before it first ever reaches the goal state.
Specifically was looking at stable_baselines3'...
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Most of state-action pairs remain unvisited in the q-table
In building my first Q-learning algorithm for OpenAI gym's CartPole problem, many of my states remain unvisited. I believe it is the reason that my agent does not learn.
Can I be told of the reasons I ...
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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 ...
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Why isn't my implementation of DQN using TensorFlow on the FrozenWorld environment working?
I am trying to test DQN on FrozenWorld environment in gym using TensorFlow 2.x. The update rule is (off policy)
$$Q(s,a) \leftarrow Q(s,a)+\alpha (r+\gamma~ max_{a'}Q(s',a')-Q(s,a))$$
I am using an ...
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Is it possible to use Reward Function of type R(s, a, s') if more than one action is applied?
I am applying a reinforcement learning agent (PPO2, stable baselines implementation) to a custom built environment using OpenAI Gym. One reward function (formualted as loss function, that is, all ...
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How to normalize input data to Reinforcement learning platform (Gym and stable-baselines)
I created a custom environment with Gym and trained it with stable baseline 3 algorithms.
The observation and space action are both continues.
The observation space includes 10 values and action space ...
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What method is better to use for a two-player reinforcement learning environment?
I want to create an RL agent for a mancala-type two-player game as my first actual project in the field. I've already completed the game itself and coded a minimax algorithm.
The question is: how ...
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Too slow search using MCTS in OpenAI Atari games
I'm recently using Monte Carlo Tree Search in OpenAi Gym Atari, but the result isn't satisfying.
Without render, the game lasts about 180 steps ( env.step() was called this much time ) with random ...
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Why does Q-value become negative during training of DQN, while the agent learns to play?
I have implemented a simple version of the DQN algorithm for CartPole-v0. The algorithm works fine, in the sense that achieves the highest possible scores. The ...
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Difference in average rewards between taking random actions and following random policies
I wrote two programs that simulated 10000 episodes in gym environment CartPole-v0.
The first program takes random moves in every steps in each episode. The average reward over 10000 episodes is 22....
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How to deal with KerasRL DDPG algorithm getting stuck in a local optima?
I am using KerasRL DDPG to try to learn a policy on my own custom environment, but the agent is stuck in a local optima although I am adding the OrnsteinUhlenbeck randomization process. I used the ...
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OpenAI gym's CartPole problem system does not learn
My OpenAI CartPole-v0 problem's implementation using basic Q-learning does not learn at all.
I am a beginner and have implemented my first ever Q-learning from scratch after learning from tutorials.
...
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Reinforcement learning - calculating policy gradient using cross entropy loss
I am writing a program that uses reinforcement learning and the policy gradient method to play Pong. It basically extends Andrej Karpathy's version (https://gist.github.com/karpathy/...
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DDPG input incompatible in OpenAI Gym custom environment
I have a custom OpenAI Gym Boid flocking environment using StableBAselines3 for DDPG. This error I encounter occurred previously due to wrong input size of actions. But my reset function is correct, ...
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Also is there any way to create a gym environment that can be used without registering?
Please see the title: is there any way to create a gym environment that can be used without registering?
To be specific, since we have already created the environment class, is there any way to ...
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Offline CartPole on infinitely long line?
I am tentatively exploring some RL research that involves doing offline RL on a version of the Gymnasium CartPole where the cart can move on $\mathbb R$, as opposed to the standard version (see link) ...
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Deep Reinforcement Learning that takes action from two different sets
I am working on a problem where I want to schedule multiple activities (a1, a2, a3, ... aN) requiring different resource types ...
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Using deep reinforcement learning for malware detection; trained agent mostly performs the same action
I'm trying to implement this article:
Ransomware early detection using deep reinforcement learning on portable executable header
The article uses an unpublished dataset of benign and ransomware ...
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Changing Gym Environment Mid Training
I am using a custom gym environment for a research project. As my agent solves the environment, I want the task to get progressively harder. Right now, I am doing that like so:
...
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328
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Tips for solving OpenAI/Faramas Gymnasium Car Racing Environment
Im quite new to ML and wanna solve Gyms Car Racing v2 using Q-Learning with a Q-Table.
But I am having problems approaching this. Thats why I am hoping someone more advanced in this field could give ...
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Time taken to solve cartpole environment using DQN
I am trying to solve the cartpole environment (GitHub) using DQN agent. I have been building my own DQN agent by following a tutorial by Jon Krohn.
I am able to solve the environment with a maximum ...
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CartPoleV0 model is not getting trained in even after 1500+ episodes using deep Q-learning
I am new to deep Q learning and trying to train the open AI cartpole_V0 game using deep Q learning. Here is my code:
...
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192
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Open AI Taxi - Agent fails to learn an effective policy
I'm trying to solve the openai gym taxi problem (v3) using deep q learning. I've already had some success with the q-table approach, but for the life of me cannot manage to train a NN to learn a ...
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Is is not possible to achieve average reward of more than 20-40 with simple Q-Learning
I have implemented the simple Q-Learning based solution for AI-gym's Cartpole-v0.
However, despite changing hyper-parameters, and rechecking my code, I cannot get an average reward (N-running reward) ...
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