Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author |
user:1234 user:me (yours) |
| Score |
score:3 (3+) score:0 (none) |
| Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections |
title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status |
closed:yes duplicate:no migrated:no wiki:no |
| Types |
is:question is:answer |
| Exclude |
-[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with q-learning
Search options not deleted
user 36710
For questions related to the Q-learning algorithm, which is a model-free and temporal-difference reinforcement learning algorithm that attempts to approximate the Q function, which is a function that, given a state s and an action a, returns a real number that represents the return (or value) of state s when action a is taken from s. Q-learning was introduced in the PhD thesis "Learning from Delayed Rewards" (1989) by Watkins.
1
vote
0
answers
251
views
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.
C …
- 393
0
votes
1
answer
805
views
How can I change observation states' values in OpenAI gym's cartpole environment?
I am learning with the OpenAI gym's cart pole environment.
I want to make the observation states discrete (with small stepsize) and for that purpose, I need to change two of the observations from [$
- …
- 393
2
votes
0
answers
229
views
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 …
- 393
-1
votes
Is is not possible to achieve average reward of more than 20-40 with simple Q-Learning
The code to my question is as below, for reference:
import gym
import numpy as np
import matplotlib.pyplot as plt
# Discretize the contiuous space
DISCRETE_POINTS = 50
X_position = np.linspace(-2.4, …
- 393
0
votes
0
answers
143
views
Strange behavior of Q-learning agent after being trained
I built a simple X*Y grid world environment to learn and then trained my agent over it. All worked fine and the agent learned as well. Let me give some detail about the environment.
Environment:
A 4x …
- 393
0
votes
1
answer
166
views
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) …
- 393