Tabular methods for reinforcement learning
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Updated
Jul 3, 2020 - Python
Tabular methods for reinforcement learning
Demonstration of Q-Learning and SARSA algorithms utilizing Python and OpenAI GYM
Implementation of SARSA algorithm for path planning
Open Gym Taxi v3 environment solved using sarsamax algorithm(Q-Learning)
path planning using Q learning algorithm
Temporal Difference methods - A simple implementation of SARSA algorithm applied to OpenAI gym's "CliffWalking" environment.
The following project concerns the development of an intelligent agent for the famous game produced by Nintendo Super Mario Bros. More in detail: the goal of this project was to design, implement and train an agent with the Q-learning reinforcement learning algorithm.
Solutions for OpenAI Gym RL environments
Applying PBT optimization technique to different domains
This github contains a simple OpenAi Gym Maze Enviroment and (at now) a RL Algorithm to solve it.
OpenAI_gym_Taxi-v2 solved with reinforcement learning - Expected Sarsa
Pac-Man RL Agent
Reinforcement learning algorithm implements.
The implementation of some reinforcement learning techniques like (Q-learning, SARSA, DQN) in two assignments and one big project.
人工智能课程的实验
Two reinforcement learning algorithms (Standard SARSA Control and Tabular Dyna-Q) where an agent learns to traverse a randomly generated maze
University of Tehran-Reinforcement Learning Fall 2022
Implementation of an agent capable of playing a simplified version of the blackjack game using SARSA algorithm.
Implementation of certain crucial algorithms in the field of reinforcement learning.
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