Questions tagged [open-ai]
For questions related to the openAI, including the Gym toolkit.
31
questions with no upvoted or accepted answers
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How did the OpenAI 5 for Dota concatenate units?
I am no expert in the field of AI so I apologize if this is a simple/easy question. I was trying to implement a network similar to OpenAI's for another game and I noticed that I did not fully ...
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How is ChatGPT maintaining context?
It has been suggested in the answer to this earlier question that it is just remembering a certain amount of recent information. The reference used is this post by OpenAI which says that ChatGPT ...
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183
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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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What is a high performing network architecture to use in a PPO2 MlpLnLstmPolicy RL model?
I am playing around with creating custom architectures in stable-baselines. Specifically I am training an agent using a PPO2 model.
My question is, are there some rules of thumb or best practices in ...
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547
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How many episodes does it take for a vanilla one-step actor-critic agent to master the OpenAI BipedalWalker-v2 problem?
I'm trying to solve the OpenAI BipedalWalker-v2 by using a one-step actor-critic agent. I'm implementing the solution using python and tensorflow.
I'm following this pseudo-code taken from the book ...
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Can GPT-3 write an entire program if provided with detailed UML and ER Diagrams?
We already have tools like Denigma.app & Figstack.com (AI-powered code explanation in English), Codesee.io (Codebase and dependency mapping).
There's also a tool called Enzyme.so which converts ...
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244
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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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27
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What is the meaning of "Our current objective weights every token equally and lacks a notion of what is most important to predict" in the GPT-3 paper?
On page 34 of OpenAI's GPT-3, there is a sentence demonstrating the limitation of objective function:
Our current objective weights every token equally and lacks a notion of what is most important to ...
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110
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How should I simulate this Markov Decision Process?
I am working on solving a problem on nodes in a graph communicating with each other. They try to estimate a central state using Kalman consensus filter, with the connections described by the graph's ...
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212
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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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What is the difference between step_model and train_model in the OpenAI implementation of the A2C algorithm?
I'm struggling a little with understanding the OpenAI implementation of A2C in the baselines (version 2.9.0) package. From my understanding, one ...
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179
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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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1
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0
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70
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State-of-the-art algorithms not working on a custom RL environment
I'm trying to train a RL agent on a custom, highly stochastic environment (MDP). In order to do so I'm using existing implementations of state-of-the-art RL algorithms as provided by Stable Baselines. ...
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1
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181
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How do i start building an autoclick bot for pubg mobile?
I want to make a bot which clicks the fire button on the mobile screen upon seeing an enemies head.
In pubg mobile which is an android game you have to control the fire button and the aim along with ...
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vote
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88
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Same implementation, but agent is not learning in Retro Pong Environment
I tried to implement the exact same python coding by Andrej Karpathy to train RL agent to play Pong, except that I migrated the environment from Gym to Retro.
Everything is the same except the action ...
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1
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28
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How am I getting same results 30 times faster than in original HER paper?
I am reproducing the results from Hindsight Experience Replay by Andrychowicz et. al. In the original paper they present the results below, where the agent is trained for 200 epochs.
200 epochs * 800 ...
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167
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Understanding policy update in PPO2
I have a question regarding the functionality of the PPO2 algorithm together with the Stable Baselines implementation:
From the original paper I know that the policy parameters $\theta$ are updated K-...
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2
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203
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Running 2 NEAT nets on the same observations
So i have been playing around with neat-python. I made a program, applying neat, to play pinball on the Atari 2600. The code for that can be found in the file ...
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17
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Using embedings to answer questions
i have simple code. text which is indexed in pinecone. when person asks quesiton i'm searching for relevant part from this index and then givin this part to open ai to answer question based on this ...
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When would you use prompting vs. fine tuning?
I would like to hear your thoughts on when is it appropriate to use prompting vs. fine-tuning.
Does one make more sense for specific tasks than the other.
Kindly elaborate.
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25
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What is a good strategy for breaking up content into prompts and completions for OpenAI fine tuning?
I want to train a fine-tuned openai model to know more about specific Judo throws and training methodologies. I have a bunch of documents I have written on Judo throws that I would like to use for ...
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895
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What are the similarities and differences between ChatGPT and YouChat?
I have recently tried the both, and it looks to me that the both have similar capabilities.
YouChat says ChatGPT is more advanced.
YouChat has connection to the Internet, and according to it, ...
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Is there a way to determine if code has been autogenerated by an AI source?
Lately, our Junior developer has been producing code fixes very quickly. At first, I was excited for him as I thought he was starting to retain information and proving he was able to research and fix ...
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Does ChatGPT's limited understanding of novel inputs reveal limitations in language's ability to convey meaning?
As a language model, ChatGPT generate responses based on patterns they have learned from the data they were trained on. However, it may not always provide a perfect or complete answer to novel or ...
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50
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Embedding layers/entities in openAI's Hide and seek paper
I've recently come across a youtube video about openAI's hide and seek paper (https://openai.com/blog/emergent-tool-use/) and got really fascinated about the paper itself. But as I digging in the ...
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206
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Problem with OpenAI gym in VSCode
I downloaded OpenAI Gym in windows from the console, it did not give me any error, but when I run the file nothing is shown as can be seen in the terminal. So I don't know what to do or what to ...
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21
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How to utilize real-world data to improve performance of RL Agent?
I'm still a newbie in RL, so please forgive me if the answer is obvious or the question totally dumb.
I'm currently trying to train a robot RL agent in OpenAI gym with a custom environment. This alone ...
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0
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49
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Dall-E Question (probably silly)
I have started to read the Dall-E (1) paper and I have a quick question that will help me a lot. I know the basis of Transformers but only for NLP tasks (Text-to-text).
So when i read : "The ...
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198
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Why DDPG losses don't decrease while the reward grows?
I've noticed that training a DDPG agent in the Reacher-v2 environment of OpenAI Gym, the losses of both actor and critic first decrease but after a while start increasing but the episode mean reward ...
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156
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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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0
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119
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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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