SARSA, Q-Learning, Expected SARSA, SARSA(λ) and Double Q-learning Implementation and Analysis
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Updated
Aug 19, 2019 - Python
SARSA, Q-Learning, Expected SARSA, SARSA(λ) and Double Q-learning Implementation and Analysis
Implementations of various RL and Deep RL algorithms in TensorFlow, PyTorch and Keras.
Autonomous Navigation of MAVs using Reinforcement Learning algorithms
An a bias-variance tradeoff of Sarsa vs. Expected Sarsa with experiments.
This repository has RL algorithms implemented using python
Solving Markov Decision Process using Value Iteration and Policy Iteration, SARSA, Expected SARSA and Q-Learning
A reinforcement learning framework for the game of Nim.
Various fundamental reinforcement learning algorithms implemented from scratch
Reinforcement Learning (COMP 579) Project
Reversi game with multiple reinforcement learning algorithms.
Advanced RL algorithms for two simplified versions of chess. Shortest Path finds the minimal moves between two cells based on piece capabilities. Capture Pieces trains against random opponents aiming for maximal captures in set moves. Features Deep Q-Learning, Policy Iteration, TD and more.
This repo contains python implementation to the cliff walking problem from RL Introduction by Sutton & Barto Example 6.6.
Using deep expected sarsa with tensorflow to solve the lunar lander problem with hyperparameter tuning and results analysis
Implementation of Q-Learning and Expected SARSA algorithms to solve the Text-Flappy-Bird game
Neural Expect Sarsa Reinforcement Learning Agent for Snake
Implementation of TD Learning algorithms for Drone Parrot for TCS Project
Some of my solutions of the exercises and all my projects of the Udacity Deep Reinforcement Learning Nanodegree https://www.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893
Exercise and assignments of Deep Reinforcement Learning Nanodegree Program offered by Udacity
An Expected SARSA RL agent created to solve the Mountain Car problem.
Compare q-learning, SARSA and Expected SARSA to solve AI gym's Taxi-v3 environment
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