PoE AI Part 4: Real-time Screen Capture and Plumbing

This post is the forth part of a series on creating an AI for the game Path of Exile © (PoE).

  1. A Deep Learning Based AI for Path of Exile: A Series
  2. Calibrating a Projection Matrix for Path of Exile
  3. PoE AI Part 3: Movement and Navigation
  4. PoE AI Part 4: Real-Time Screen Capture and Plumbing
  5. AI Plays Path of Exile Part 5: Real-Time Obstacle and Enemy Detection using CNNs in TensorFlow

As discussed in the first post of this series, the AI program takes a screenshot of the game and uses it to form predictions that are then used to update its internal state. In this post, efficient methods for capturing images of the game screen are explored.

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Introducing GopherJoy: A Controller Input Application

So, I was looking for a way to use my XBox 360 Controller for Windows to browse the web and play games without built-in controller support. After searching for a while, I found most existing applications were either not free or did not work very well. Some required extra dll files (pro-tip DON’T search for “[insert name].dll missing” and download the first thing you find), or were not fully functional. Having experience handling mouse and keyboard input using Windows API, I decided to see if I could come up with something better. The result: GopherJoy.

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A Deep Learning Based AI for Path of Exile: A Series

This post is the first in a series on creating an AI for the game Path of Exile based on deep learning and other machine learning techniques. A list of posts in this series follows.

  1. A Deep Learning Based AI for Path of Exile: A Series
  2. Calibrating a Projection Matrix for Path of Exile
  3. PoE AI Part 3: Movement and Navigation
  4. PoE AI Part 4: Real-Time Screen Capture and Plumbing
  5. AI Plays Path of Exile Part 5: Real-Time Obstacle and Enemy Detection using CNNs in TensorFlow

The goal of the project is to create an AI that operates based on visual input, is able to navigate levels successfully, can defend itself, and of course to have fun and learn something in the process.

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Visualizing Neural Network Performance on High-Dimensional Data

This post is part of a series on artificial neural networks (ANN) in TensorFlow and Python.

  1. Stock Market Prediction Using Multi-Layer Perceptrons With TensorFlow
  2. Stock Market Prediction in Python Part 2
  3. Visualizing Neural Network Performance on High-Dimensional Data
  4. Image Classification Using Convolutional Neural Networks in TensorFlow

This post presents a short script that plots neural network performance on high-dimensional binary data using MatPlotLib in Python. Binary vectors, or vectors only containing 0 and 1, can be useful for representing categorical data or discrete phenomena. The code in this post is available on GitHub.

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