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Creation of grid world environment through pygame package and optimizing the motion of agent through modified q-learning process. Video can be found here: https://www.youtube.com/watch?v=-nXH8k9gRLM
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.
Coastal infrastructure adaptation against climate change effects is often addressed with policies that ignore future climate uncertainties. This work develops a climate change adaptation framework, offering optimal solutions that address model uncertainty, social costs of carbon, and a variety of adaptation actions.