Sample Policy Gradient
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Updated
Oct 31, 2021 - Python
Sample Policy Gradient
Project for the course "Foundations of Reinforcement Learning" 2021 at ETH Zurich
[Innopolis University] Reinforcement Learning Course 2022.
A Pytorch implementation of The Visual Centrifuge: Model-Free Layered Video Representations.
Implementation of k-Step Latent (KSL)
Network inference via Event Space Linearization (ESL)
This presentation contains very precise yet detailed explanation of concepts of a very interesting topic -- Reinforcement Learning.
This repository hosts the code accompanying the paper "Model-Free Active Exploration in Reinforcement Learning". Our study approaches the exploration problem in Reinforcement Learning (RL) from an information-theoretical viewpoint and presents a novel, efficient, and entirely model-free solution.
Program an agent to learn the optimal route through a maze using reward-based action selection
DDPG and D4PG Continuous Control
Deep Reinforcement Learning implementation in Keras of an AI controlling the popular Flappy Bird videogame, using Asynchronous Advantage Actor Critic (A3C)
A Python package for Robot Learning
Implementation of Soft Actor Critic and some of its improvements in Pytorch
Code for IEEE MLSP 2021 paper titled "Model-Free Learning of Optimal Deterministic Resource Allocations in Wireless Systems via Action-Space Exploration"
Implementation of the CartPole from OpenAI's Gym using only visual input for Reinforcement Learning control with DQN
Curvature Corrected Moving Average: An accurate and model-free path smoothing algorithm.
Customisable Unified Physical Simulations (CUPS) for Reinforcement Learning. Experiments run on the ai2thor environment (http://ai2thor.allenai.org/) e.g. using A3C, RainbowDQN and A3C_GA (Gated Attention multi-modal fusion) for Task-Oriented Language Grounding (tasks specified by natural language instructions) e.g. "Pick up the Cup or else"
ExORL: Exploratory Data for Offline Reinforcement Learning
The Reinforcement-Learning-Related Papers of ICLR 2019
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
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