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https://github.com/fonnesbeck/nctc_course
Markov Decision Processes and Dynamic Optimization module at NCTC, March 2015
https://github.com/fonnesbeck/nctc_course
Last synced: 28 days ago
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Markov Decision Processes and Dynamic Optimization module at NCTC, March 2015
- Host: GitHub
- URL: https://github.com/fonnesbeck/nctc_course
- Owner: fonnesbeck
- Created: 2015-03-11T20:49:03.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2015-03-19T17:29:38.000Z (over 9 years ago)
- Last Synced: 2023-03-12T03:53:01.891Z (over 1 year ago)
- Language: CSS
- Size: 410 KB
- Stars: 5
- Watchers: 3
- Forks: 9
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Markov Decision Processes and Dynamic Optimization
Course module for Decision Analysis Tools course, March 2015 at the National Conservation Training Center
A static HTML version of this tutorial can be viewed [here](http://bit.ly/nctc_mdp). To run the tutorial yourself on your own machine, follow the installation instructions below.
## Installing Python and Required Packages
### Step 1: Install Python (Anaconda)
The easiest way to install the Python packages required for this tutorial is via [Anaconda](https://store.continuum.io/cshop/anaconda/), a scientific Python distribution offered by Continuum analytics. [Download Anaconda](http://continuum.io/downloads "Download Anaconda Python Distribution"), and run the installer.
### Step 2: Update packages
Once Anaconda is installed, there are a few steps required to install the packages that the tutorial uses. From your command line terminal, enter the following commands:
conda update ipython ipython-notebook pandas pip
pip install pymdptoolbox filterpy
### Step 3: Acquire course materials
When these have been installed, the next step is to download the tutorial materials. For those of you familiar with Git, you can simply clone the [GitHub repository](https://github.com/fonnesbeck/NCTC_course) to your machine. If you are unfamiliar with Git, you may download a [zip archive](https://github.com/fonnesbeck/NCTC_course/archive/master.zip) to your machine instead, and extract the files therein to a location of your choice.
### Step 4: Run IPython Notebook
The tutorial is contained in an IPython Notebook, an interactive interface for running code alongside the notes for the tutorial. IPython Notebooks are identified by a `.ipynb` extension on the file. There are two ways of starting up the notebook:
1. **From the command line**: In your command line terminal, move into the folder that you extracted the tutorial files to, and run:
ipython notebook
This should open your default browser, and show a list of files within the IPython Notebook interface. Then you should be able to double-click on the `Markov Decision Processes and Dynamic Optimization.ipynb` file to open the tutorial.
2. **Using the Anaconda launcher**: Anaconda may have created an icon labelled "Launcher" on your desktop, or in your Applications folder. Double clicking on this should bring up an interface with several options:
Select the IPython Notebook, which should open your default browser, and show a list of files within the IPython Notebook interface. Then you should be able to double-click on the `Markov Decision Processes and Dynamic Optimization.ipynb` file to open the tutorial.
