A random environment reinforcement learning-powered Mario game
I am trying to implement various AI algorithms on various environments (like OpenAI-gym) as I learned my toward the safe AI
A reinforcement learning framework
A game using Q-Learning artificial intelligence.
LR Micro mouse AI trains itself using Q-learning algorithm to find the most optimal path through a randomly generated maze.
A modernized, interactive demo of value iteration in a 10×10 grid world, adapted from David Poole’s original demo. Visualizes how the value function and optimal policy evolve with each iteration.
simple self driving car application
Personal implementation in C++ of http://www.cs.put.poznan.pl/mszubert/pub/szubert2014cig.pdf. Results could be reproduced. It's an algorithm that learns by itself to solve the 2048 game. It doesn't use deep learning (aka. neural networks). But it learns by itself using the Bellman equations.
To use A star search algorithm to find the shortest path between nodes or graphs and use this as a pathfinder. It is an informed search algorithm, as it uses information about path cost and also uses heuristics to find the solution.
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