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.
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.
Code for some fun exercises in the textbook 'Reinforcement Learning - An Introduction'
Reinforcement Learning Project - Mountain Car
Sutton's Mountain Car Problem with Value Iteration
University Course Assignment - Reinforcement Learning
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.
Double deep q network implementation in OpenAI Gym's "Mountain Car" environment
This repository contains codes of deep deducing solving the classic control problems.
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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