I came across Alex Wissner-gross and his theory of intelligent behavior in his Ted Talk linked Here. I have tried to read the scholastic paper linked Here, which is associated with his presentation, but I don’t have enough comprehension of the math and physics to really understand what’s going on, and more importantly, how I can reproduce this equation in python.
There are a couple unique models for entropy maximization I found that are implemented in python, but I don't know how to set them up and whether they are identical to Wissner-gross’s equation.
Scipy: MaxEntropy
MEMT: Tutorial | Homepage
Assuming these equations are different forms of Wissner's equation and using a library above or some other library, how do I set up an entropy maximization algorithm.
Particularly,
The question is quite general, and unfortunately I don't think this answer will give you as much of a solution that you may had hoped for.
First of all, it seems that your assumption that "these equations are different forms of Wissner's equation" is a bad one.
Having browsed through the paper, it does seem that the model for what they refer to as causal entropic force (F) share some components with the maximum entropy models (not surprisingly), for which you have found some libraries. However, to see how these libraries could be used in an implementation of causal entropic forcing, you will have to look at the paper and find how the different expressions match/share components. I doubt anyone in here will do that for you. The Wikipedia article about maximum entropy may help you a little bit to find the relation.
To get started with the animation and movement, I suggest you find some introduction to sprite animation, for example this one. This will help you get a sense of how to move objects around in a space using code.
Edit
The paper's supplemental material is definitely worth a look as well, even containing some pseudocode. Also, reference [12] in the paper reads as follows:
Our general-purpose causal entropic force simulation software will be made available for exploration at http://www.causalentropy.org
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