I try to use Stable Baseliens train a PPO2 with MlpPolicy. After 100k timesteps, I can only get 1 and -1 in action. I restrict action space to [-1, 1] and directly use action as control. I don't know if it is because I directly use action as control?
MlpPolicy only return 1 and -1 with action spece[-1,1]
236 Views Asked by qwererer2 At
1
There are 1 best solutions below
Related Questions in REINFORCEMENT-LEARNING
- Named entity recognition with a small data set (corpus)
- how can get SARSA code for gridworld model in R program?
- Incorporating Transition Probabilities in SARSA
- Minibatching in Stochastic Gradient Descent and in Q-Learning
- Connecting Python + Tensorflow to an Emulator in C++
- How to generate all legal state-action pairs of connect four?
- exploration and exploitation in Q-learning
- Counterintuitive results on multi-armed bandit exercise
- Deep neural network diverges after convergence
- Reinforcement learning algorithms for continuous states, discrete actions
- multiply numbers on all paths and get a number with minimum number of zeros
- Reinforcement learning in netlogo
- Parametrization of sparse sampling algorithms
- Function approximator and q-learning
- [Deep Q-Network]How to exclude ops at auto-differential of Tensorflow
Related Questions in OPENAI-GYM
- How to install OpenAI Universe without getting error code 1 on Windows?
- Installing gym[atari] in a virtualenv
- Function approximator and q-learning
- Keras input dim error
- Reinforcement Learning for classification problems?
- How to tell an agent that some actions in the action space are currently not available in gym?
- RL problem on COLAB for 'gym.envs.box2d' has no attribute 'LunarLander'
- How to simulate an object balancing on another in pybullet?
- How to install h5py with pypy?
- Difficulty with Stablebaselines VecFrameStack function for observation space pre-processing
- Unable to Use Monitor Wrapper with Atari Environments in Stable Baselines 3
- Open AI Gym: Ant not rendering
- Rendering example for deep learning
- Unable to see SuperMarioBros env being rendered on the screen
- I'm trying to use gym_super_mario_bros and it's giving me this error: ValueError: not enough values to unpack (expected 5, got 4)
Related Questions in POLICY-GRADIENT-DESCENT
- MlpPolicy only return 1 and -1 with action spece[-1,1]
- Convergence guarantee of Policy Gradient with function approximation
- ValueError: No gradients provided for any variable in policy gradient
- Reward not increasing while training a Bipedal System
- Action masking for continuous action space in reinforcement learning
- Parallel environments in Pong keep ending up in the same state despite random actions being taken
- python policy gradient reinforcement learning with continous action space is not working
- DDPG not converging for a simple control problem
- DDPG always choosing the boundaries actions
- Can the output of DDPG policy network be a probability distribution instead of a certain action value?
- How do you evaluate a trained reinforcement learning agent whether it is trained or not?
- One back-propagation pass in keras
- How to sample actions for a multi-dimensional continuous action space for REINFORCE algorithm
- How to accumulate my loss over mini batches then calculate my gradient
- Policy gradient in keras predicts only one action
Related Questions in STABLE-BASELINES
- Pytorch - RuntimeError: invalid multinomial distribution (encountering probability entry < 0)
- Simpy in combination with RL
- Difficulty with Stablebaselines VecFrameStack function for observation space pre-processing
- Add the plot of the reward function during training on Wandb dashboard using Stable baseline 3
- Unable to Use Monitor Wrapper with Atari Environments in Stable Baselines 3
- Rendering example for deep learning
- Unable to see SuperMarioBros env being rendered on the screen
- How discount factor is taken into account in stable baselines 3 on policies methods i.e. PPO?
- 'mujoco._structs.MjData' object has no attribute 'solver_iter'
- n_state, reward, done, info = env.step(action) returns value error
- PPO Boid agent not learning
- StableBaselines3 Significant Difference between Evaluation and Testing Reward
- IndexError while making predictions with model.predict using PPO and custom OpenAI Gym
- Trained RL Cartpole model produces poor reward using Stable-baseline
- Gymnasium environment consisting of multiple environments
Related Questions in MUJOCO
- MuJoCo dm_control: modifying the name of an element imported from an XML file
- 'mujoco._structs.MjData' object has no attribute 'solver_iter'
- Creating custom XML shortcut in Mujoco
- How to downgrade Mujoco version?
- Position control in Mujoco
- How to include GTK library for MuJoCo simulation in Visual Studio Code (Windows10)
- Mujoco: `gym.error.DependencyNotInstalled: dynamic module does not define module export function (PyInit_cymj)`
- MlpPolicy only return 1 and -1 with action spece[-1,1]
- Install mujoco for C++
- MUJOCO_PY:Computed torque control for kuka iiwa14 robot
- Error:ValueError: Buffer has wrong number of dimensions (expected 1, got 2)
- Failed building wheel for mujoco-py
- Getting `Exec format error` when trying to patch MuJoCo binaries with patchelf
- Is there a convenient way to dynamically create constraints between two bodies in MuJoCo?
- Mujoco installation, binaries not found
Trending Questions
- UIImageView Frame Doesn't Reflect Constraints
- Is it possible to use adb commands to click on a view by finding its ID?
- How to create a new web character symbol recognizable by html/javascript?
- Why isn't my CSS3 animation smooth in Google Chrome (but very smooth on other browsers)?
- Heap Gives Page Fault
- Connect ffmpeg to Visual Studio 2008
- Both Object- and ValueAnimator jumps when Duration is set above API LvL 24
- How to avoid default initialization of objects in std::vector?
- second argument of the command line arguments in a format other than char** argv or char* argv[]
- How to improve efficiency of algorithm which generates next lexicographic permutation?
- Navigating to the another actvity app getting crash in android
- How to read the particular message format in android and store in sqlite database?
- Resetting inventory status after order is cancelled
- Efficiently compute powers of X in SSE/AVX
- Insert into an external database using ajax and php : POST 500 (Internal Server Error)
Popular Questions
- How do I undo the most recent local commits in Git?
- How can I remove a specific item from an array in JavaScript?
- How do I delete a Git branch locally and remotely?
- Find all files containing a specific text (string) on Linux?
- How do I revert a Git repository to a previous commit?
- How do I create an HTML button that acts like a link?
- How do I check out a remote Git branch?
- How do I force "git pull" to overwrite local files?
- How do I list all files of a directory?
- How to check whether a string contains a substring in JavaScript?
- How do I redirect to another webpage?
- How can I iterate over rows in a Pandas DataFrame?
- How do I convert a String to an int in Java?
- Does Python have a string 'contains' substring method?
- How do I check if a string contains a specific word?
This could be the result of the gauß distribution PPO2 is using. You could use a different algorithm that doesn't use gauß or use PPO with another distribution.
Checkout the example here: https://github.com/hill-a/stable-baselines/issues/112 And this paper: https://www.ri.cmu.edu/wp-content/uploads/2017/06/thesis-Chou.pdf