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First I would like to discuss our goals and long-term plans. We want to create an artificial intelligence that learns how to play first-person shooters without access to any game state data other than what can be gained through the audio and visual buffers. In other words, the AI will only have access to the information that a human player would. If we are successful with these constraints, then I could see our work leading to AI that can play any game, or even AI-driven robots that can play games using mechanical hands and eyes to operate normal peripherals and interfaces. We are currently in the research and planning phase of the project. This means that our job right now is to decide exactly what tools and technologies we will use and how they will interact with one another. By the end of the semester, which will arrive sometime this December, we will need to be ready for phase two, which is the development, training, and testing phase. Yes, that is all three at once. However, if...

Over the past couple of weeks, Matthew and I have been trying to narrow down our idea for capstone. We have settled on a "Modular" AI that can play First Person Shooters or other similar video games. However, we decided to put a slight twist on the idea of an AI playing games. Most of the AIs that are currently out have more information than they should possibly have at that time, like the location of players. We decided that our AI would only have information that would be accessible to a human player. We also noticed that many of the "PlayerAIs" out there are reactionary, not planning. While reacting is a key part to many of these games, so is strategy. We want to create an AI that thinks, at least a little bit, about that actions it is making or should make. Since narrowing down our topic we have split off and started looking at different existing technologies and research that could help us understand and create this project. I decided to look at some comp...