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Diffusion for World Modeling is an experimental reinforcement learning system that trains intelligent agents inside a simulated environment generated by a diffusion-based world model. The project introduces the idea of using diffusion models, commonly used for image generation, to simulate the dynamics of an environment and predict future states based on previous observations and actions. Instead of interacting directly with a real environment, the reinforcement learning agent learns within...
This really isn't a game. It's all very randomly generated, and there is no way for any user input. I'll consider putting some in later.
I had been wanting to make the Game of Life for some time as well as make some kind of genetic algorithm based code.
So, here is what I came up with. While this may just seem like simplify a graphical display of what boredom looks like... well, it really doesn't go much past that point.
If you Don't know what Conway's game of life is:
It's the...
This project gives you a simple 2D world for playing with Artificial Intelligent actors. It contains of a world with objects. And a simple game, pyRugby, demonstrating the use of this world. All built in Python, using pygame for visualization.
General purpose agents using reinforcement learning. Combines radial basis functions, temporal difference learning, planning, uncertainty estimations, and curiosity. Intended to be an out-of-the-box solution for roboticists and game developers.
A lightweight and fast implementation of Conway\'s Game of Life and related cellular automata.
It includes a pattern viewer running X Windows and
a Python module intended to help in designing complex patterns.