AI-Toolbox
A C++ framework for MDPs and POMDPs with Python bindings (by Svalorzen)
BayesOpt
BayesOpt: A toolbox for bayesian optimization, experimental design and stochastic bandits. (by rmcantin)
| AI-Toolbox | BayesOpt | |
|---|---|---|
| 2 | 1 | |
| 641 | 379 | |
| - | - | |
| 5.1 | 1.1 | |
| 4 months ago | about 1 year ago | |
| C++ | C++ | |
| GNU General Public License v3.0 only | GNU Affero General Public License v3.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
AI-Toolbox
Posts with mentions or reviews of AI-Toolbox.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-10-02.
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Impact of using sockets to communicate between Python and RL environment
Makes sense. I was just wondering if someone had any comparisons to share. I will create a toy environment in Unreal and compare integrating RL C++ libraries (looking at AI-Toolbox and mlpack) vs using Python with socket communication.
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Greedy AI agents learn to cooperate
I maintain a repository of many implementations of classical (tabular) RL algorithms [1] which you might enjoy playing with when starting out. I use it for both research and for student projects. The advantage of avoiding NNs when starting out is that it is much simpler to inspect the inner workings of an algorithm to see whether it's working or not.
I'm always happy to help if something is unclear or difficult so feel free to open issues there :)
[1]: https://github.com/Svalorzen/AI-Toolbox
BayesOpt
Posts with mentions or reviews of BayesOpt.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-06.
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The Evolutionary Computation Methods No One Should Use
Very interesting to see how wide spread this is. Stumbled upon it myself by accident when comparing my algorithm to a popular Bayesian optimisation algorithm (https://github.com/rmcantin/bayesopt). Almost every run it would sample the exact centre of the optimisation space. At first I was blown away by the performance until I found it suspicious that the precise optimum was found so often. Shifting the optimum away from the centre greatly reduced the algorithms performance.
What are some alternatives?
When comparing AI-Toolbox and BayesOpt you can also consider the following projects:
Recast/Detour - Industry-standard navigation-mesh toolset for games
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Veles - Distributed machine learning platform
tensorflow - An Open Source Machine Learning Framework for Everyone
tiny-cnn - header only, dependency-free deep learning framework in C++14
nano
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
Native System Automation - Native cross-platform system automation
btsk - Behavior Tree Starter Kit