HXK-Only's repositories
book-recommendation-system
a simple book recommendation application
BayesOpt_Attack
Targeted black-box adversarial attack using Bayesian Optimization
botorch
Bayesian optimization in PyTorch
ContinuousParetoMTL
[ICML 2020] PyTorch Code for "Efficient Continuous Pareto Exploration in Multi-Task Learning"
CrowdNav
[ICRA19] Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning
DBRL
Dataset Batch(offline) Reinforcement Learning for recommender system
Deep-Reinforcement-Learning-Algorithms-with-PyTorch
PyTorch implementations of deep reinforcement learning algorithms and environments
Deep-reinforcement-learning-with-pytorch
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
deep_rl
PyTorch implementations of Deep Reinforcement Learning algorithms (DQN, DDQN, A2C, VPG, TRPO, PPO, DDPG, TD3, SAC, ASAC, TAC, ATAC)
GenerativeAdversarialUserModel
Tensorflow implementation for "Generative Adversarial User Model forReinforcement Learning Based Recommendation System"
MAAC
Code for "Actor-Attention-Critic for Multi-Agent Reinforcement Learning" ICML 2019
MOBO
constrained/unconstrained multi-objective bayesian optimization package.
MOBOpt
Multi-objective Bayesian optimization
Model-Based-Reinforcement-Learning-for-Online-Recommendation
A pytorch implementation of A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation.
open_spiel
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
ParetoMTL
Code for Neural Information Processing Systems (NeurIPS) 2019 paper: Pareto Multi-Task Learning
PGMORL
[ICML 2020] Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control
POMDPy
POMDPs in Python.
risk-and-uncertainty
Code associated with our paper "Estimating Risk and Uncertainty in Reinforcement Learning"
SA_DDPG
[NeurIPS 2020] State-adversarial DDPG for robust deep reinforcement learning
SD-GAR
This repository hosts the experimental code for NeurIPS 2020 paper "Sampling-Decomposable Generative Adversarial Recommender".
StateAdvDRL
[NeurIPS 2020, Spotlight]Code for "Robust Deep Reinforcement Learning against Adversarial Perturbations on Observations"
Transformers-RL
An easy PyTorch implementation of "Stabilizing Transformers for Reinforcement Learning"
TransGAN
[NeurIPS‘2021] "TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up", Yifan Jiang, Shiyu Chang, Zhangyang Wang