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ai-safety-gridworlds

This is a suite of reinforcement learning environments illustrating various safety properties of intelligent agents.

awesome-rl-competitions

List of competitions related to Reinforcement Learning

citylearn

code-for-paper

cpo

Constrained Policy Optimization

cs285_fa19_deep_reinforcement_learning

My solutions to UC Berkeley CS285 (originally CS294-112, deeprlcourse) Fall 2019 assignments

cudnn.torch

Torch-7 FFI bindings for NVIDIA CuDNN

d3rlpy

An offline deep reinforcement learning library

deep-reinforcement-learning-with-pytorch

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

detect-the-common-of-images

implementation of "Matching local self-similarities across images and videos"

dirichlet

Dirichlet MLE python library

drl-for-microgrid-energy-management

We study the performance of various deep reinforcement learning algorithms for the problem of microgrid’s energy management system. We propose a novel microgrid model that consists of a wind turbine generator, an energy storage system, a population of thermostatically controlled loads, a population of price-responsive loads, and a connection to the main grid. The proposed energy management system is designed to coordinate between the different sources of flexibility by defining the priority resources, the direct demand control signals and the electricity prices. Seven deep reinforcement learning algorithms are implemented and empirically compared in this paper. The numerical results show a significant difference between the different deep reinforcement learning algorithms in their ability to converge to optimal policies. By adding an experience replay and a second semi-deterministic training phase to the well-known Asynchronous advantage actor critic algorithm, we achieved considerably better performance and converged to superior policies in terms of energy efficiency and economic value.

dyna-gym

This is a pip package implementing Reinforcement Learning algorithms in non-stationary environments supported by the OpenAI Gym toolkit.

effective-dsm

Effective Consumption Scheduling for Demand-Side Management in the Smart Grid using Non-Uniform Participation Rate

finglm

gitskills

gnu-rl

A precocial reinforcement learning solution for HVAC control

gp-gan

Official Chainer implementation of GP-GAN: Towards Realistic High-Resolution Image Blending (ACMMM 2019, oral)

homework_fall2020

Assignments for Berkeley CS 285: Deep Reinforcement Learning (Fall 2020)

hvac-rl-control

DRP Control for HVAC

interaction-dataset

kddcup-starting-kit

The submission template for the Learning to Dispatch and Reposition Competition @ KDD2020.

lamcts

The release codes of LA-MCTS with its application to Neural Architecture Search.

lcsis

Learning cross-spectral similarity measures with deep convolutional neural networks code

learngit

lghd

Source code of LGHD: A feature descriptor for matching across non-linear intensity variations

lstm-for-trajectory-prediction

LSTM based Vehicle Trajectory Prediction

lstm_encoder_decoder

Build a LSTM encoder-decoder using PyTorch to make sequence-to-sequence prediction for time series data

mapdn

This repository is for an open-source environment for multi-agent active voltage control on power distribution networks (MAPDN).