Implementation of SARSA Semi-Gradient Method on the Mountain Car Open AI Environment.
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Updated
Dec 8, 2022 - Python
Implementation of SARSA Semi-Gradient Method on the Mountain Car Open AI Environment.
Own researches in reinforcement learning using openai-gym.
Code for some fun exercises in the textbook 'Reinforcement Learning - An Introduction'
Reinforcement Learning Project - Mountain Car
Deep Reinforcement learning applied on open AI MountainCar environment
An implementation of the paper "Reinforcement learning with a bilinear Q function" on the Mountain Car problem.
Double deep q network implementation in OpenAI Gym's "Mountain Car" environment
Sutton's Mountain Car Problem with Value Iteration
University Course Assignment - Reinforcement Learning
This repository contains codes of deep deducing solving the classic control problems.
Mountain Car is a Reinforcement Learning task that aims to learn the policy of climbing a steep hill and reaching the flag-marked goal. we use Q-learning to find the optimal policy in each case.
This repository contains implementations of Inverse Reinforcement Learning (IRL) algorithms based on the paper "Algorithms for Inverse Reinforcement Learning" - (Ng &Russell 2000)
Q Learning, SARSA, Expected SARSA to solve OpenAI's gym.mountain_car environment
Reinforcement learning algorithm implementation for "Artificial Intelligence" course project, La Sapienza, Rome, Italy, 2018
APReL: Active preference-based reward learning for human-robot interaction. Utilizing "Mountain Car" environment, learn from human preferences to reach the goal state. Applications in robotics and adaptability to other learning methods.
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