One of my earlier projects involved the development of a pathfinding algorithm for NPCs in games. The project was aimed to overcome the unfairness of NPCs in games, the unfairness of them knowing everything about the environment and you (the player) having to explore.
I HAVE MADE A NICER VERSION OF THIS HERE.
I’ve been playing about with the Perceptron in SciKit Learn but was having trouble getting to to accurately solve a linear separability problem. The problem is clearly solvable and works in Matlab, however I could not get it to work in Python. Anyways whilst writing this post, originally title ‘please help me’ I had an idea, I tested it and it worked.
So now we have a linear separability example using a single perceptron.
Over the summer I’ve been using Python for Machine Learning (ML), specifically state representation of an Atari 2600 game emulator. The project initially started with looking at this paper  which developed agents using Theano which then lead to me using the Anaconda Python package.
The package is great as it comes ready with everything most people would need to get started in Data Analysis and ML. As an example it comes ready with…
- Python 2.7 (3.x also available)
- Scikit Learn
- iPython Notebook