Comments (4)
There is nothing preventing mushroom to use any sklearn approximator that expose the fit method, particularly in fqi.
Are you sure that it is stuck? maybe it is just extremely slow the fit of the gaussian process. Try with less samples...
from mushroom-rl.
I'm not surprised at all that random trees are faster than GPs. It's normal, random trees are simply... trees. There's nothing more simple than that.
The LinearApproximator has to be used exactly as any other mushroom/sklearn approximation. Exactly as in the example.
However, FQI doesn't support features. This makes a simple linear approximator almost useless in this scenario.
In the future, we might want to reintroduce the features directly in the linear approximator. When we designed this approximator, I decided to separate the features, as many times is convenient to use them outside the approximator, but now I partially regret my decision.
If you still want to implement a linear approximator with RBF for FQI, you might want to create an approximator that before applying the linear combination, computes the features...
However, remember that FQI is designed specifically to use tree approximations, due to its algorithmic structure. If you want to use linear approximations, you should try LSPI.
from mushroom-rl.
Yeah, large sample size seems to be the issue here. Wonder how random forest is faster!
from mushroom-rl.
If one wants to use LinearApproximator class in mushroomrl as the approximator, do we need to wrap it up in Regressor class and then pass it?
from mushroom-rl.
Related Issues (20)
- Can't install package HOT 4
- suspected memory leak HOT 8
- How to train an agent in one environment and use it on another slightly different envoirnment HOT 3
- dynaq agent HOT 1
- how to reproduce DQN nature paper? HOT 7
- compress frames HOT 2
- n_steps dqn performs worse. bug? HOT 1
- support for new spaces HOT 2
- PPO for lunar lander [BUG] HOT 10
- Multi modal state support HOT 1
- Save and Load Agent for the Second Time HOT 2
- Tutorial for REINFORCE HOT 2
- REINFORCE with optional baseline HOT 1
- Incorrect Shape of Baseline in REINFORCE HOT 11
- QLearning Can't Train On Episodes HOT 6
- Suggestion: rename episodes_length to compute_episodes_length
- Suggestion: Add median to compute_metrics
- [solvers/dynamic_programming] Use np.linalg.solve instead of np.inv HOT 2
- [requirements.txt] Missing requirement for OpenAI gym HOT 4
- [Categorical DQN/Rainbow] Inconsistent behavior of Categorical DQN for an even number of atoms
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from mushroom-rl.