Experimentation on Carla Simulator for running DQN RL agents for Autonomous Driving
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Updated
Mar 17, 2020 - Python
Experimentation on Carla Simulator for running DQN RL agents for Autonomous Driving
Researching new methods to leverage Coverage and Path Planning using DeepRL
Tic Tac Toe game, designed to be used to train a Deep Neural Network via Reinforcement Learning (DQN). It can also be played by 2 humans and features a hard coded AI that never looses and will win if you do not do perfect play against it.
Reinfocement Learning Approach to solve Shortest Path Problem.
Project for AI in computer games
Deep Reinforcement Learning algorithms to play Connect4 using a combination of Supervised Learning and Reinforcement Learning
Deep Q Network with TensorFlow, used to solve CartPole environment from Gym.
comparison of q-learning and deep q-learning
This is a chatbot that I build using ChatGPT.
Training AI to play snake
Dueling DQN agents in Pong game. Pong game written by @bearpaw7
Deep reinforcement Q learning model to find the treasure at a fixed location from a random location in a maze
Deep Q-learning for playing flappy bird game
I developed and trained a deep convolutional Q-learning model to enable an agent to successfully solve the Pacman gym environment.
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