Displaying 1 to 4 from 4 results

Hands-On-Reinforcement-Learning-With-Python - Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

  •    Jupyter

Reinforcement Learning with Python will help you to master basic reinforcement learning algorithms to the advanced deep reinforcement learning algorithms. The book starts with an introduction to Reinforcement Learning followed by OpenAI and Tensorflow. You will then explore various RL algorithms and concepts such as the Markov Decision Processes, Monte-Carlo methods, and dynamic programming, including value and policy iteration. This example-rich guide will introduce you to deep learning, covering various deep learning algorithms. You will then explore deep reinforcement learning in depth, which is a combination of deep learning and reinforcement learning. You will master various deep reinforcement learning algorithms such as DQN, Double DQN. Dueling DQN, DRQN, A3C, DDPG, TRPO, and PPO. You will also learn about recent advancements in reinforcement learning such as imagination augmented agents, learn from human preference, DQfD, HER and many more.

2048-deep-reinforcement-learning - Trained A Convolutional Neural Network To Play 2048 using Deep-Reinforcement Learning

  •    Jupyter

2048 is a single-player sliding block puzzle game designed by Italian web developer Gabriele Cirulli. The game's objective is to slide numbered tiles on a grid to combine them to create a tile with the number 2048; however, you can keep playing the game, creating tiles with larger numbers. 2048 is played on a gray 4×4 grid, with numbered tiles that slide smoothly when a player moves them using the four arrow keys.Every turn, a new tile will randomly appear in an empty spot on the board with a value of either 2 or 4. Tiles slide as far as possible in the chosen direction until they are stopped by either another tile or the edge of the grid. If two tiles of the same number collide while moving, they will merge into a tile with the total value of the two tiles that collided. The resulting tile cannot merge with another tile again in the same move. Higher-scoring tiles emit a soft glow.

king-pong - Deep Reinforcement Learning Pong Agent, King Pong, he's the best

  •    Python

In this repository, you have an agent that plays the game of pong. Make no mistake though, this is not a normal player. King (the agent) has learned to play the game of pong all by himself, by looking at the screen just like you would. Now, as you can imagine, there are a lot of cutting edge technologies being mixed into this project. First, we have Computer Vision to be able to receive the percepts from the screen. Next, we have Reinforcement Learning which is part of Machine Learning, but it is not classification, nor regression, or clustering. Reinforcement Learning is inspired by the study of animal behavior. In specific, how animals react to pain, reward signals through time. King wants to win, that's why he learns to do what he does.