Purpose: The purpose of this lab is to take a "test drive" of the AIPython example code and the ipython interactive programming environment it uses by exploring a simple paper-buying agent. This agent uses the matplotlib package to graph its results.

Warmup. The lab computers have a system called Anaconda installed. Anaconda is a virtual environment for Python containing a great many machine learning and data science frameworks. The tools we use for this class are part of these frameworks.

See CSCI 415DL for the description of:

conda init

conda activate

conda deactivate

Programming Problem (5 points).

Show that you've been able to run the AIPython program agentBuying.py by generating a screenshot of the graph it produces (some of you have already done this, but for consistency I still want screenshots from everyone). You can do this on the Linux Lab computers or your own installation.

Follow these steps to get the graphs (I assume you've downloaded the AIPython zip file and expanded it into a directory):

1. Make sure you've activated your Anaconda virtual environment. If your prompt does not have the (base) prefix, run conda activate.
2. Change your directory to where you've stored the Python program.
3. Edit the file agentBuying.py by uncommenting the last 4 lines of the file (these do the simulation and plot the graph)
4. Run ipython -i agentBuying.py and screenshot the graph it produces.
5. Just looking at the graph, not the code, what do you think the agent is basing its decision to buy on? You can answer this question in the same document as your Turing Test essay.

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