An agent learns the optimal path towards its goal from any starting point while avoiding obstacles.
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Updated
Jan 24, 2024 - C#
An agent learns the optimal path towards its goal from any starting point while avoiding obstacles.
This project is a C# implementation of the popular game "Frozen Lake" and an AI agent that can play the game using the Q-learning algorithm. The game consists of a grid of tiles, some of which are safe to walk on, while others will cause the player to receive damage.
Markov Decision Process and Temporal Difference algorithms
An rougelike board game where you create the dungeon + environmental conditions and an AI agent will determine the optimal policy to traverse the dungeon to the treasure.
A Markov model builder and simulator
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