OpenDILab Decision AI Engine
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Updated
May 24, 2024 - Python
OpenDILab Decision AI Engine
Repository for our paper: "Improving Reinforcement Learning Exploration with Causal Models of Core Environment Dynamics". (submitted to ECAI 2024)
The GitHub repository for "Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo", AISTATS 2024.
The official code release for Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo, ICLR 2024.
Deep Intrinsically Motivated Exploration in Continuous Control
Code for NeurIPS 2022 paper Exploiting Reward Shifting in Value-Based Deep RL
Code to reproduce the experiments in Sample Efficient Reinforcement Learning via Model-Ensemble Exploration and Exploitation (MEEE).
Python implementations of contextual bandits algorithms
Official implementation of LECO (NeurIPS'22)
An Optimistic Approach to the Q-Network Error in Actor-Critic Methods
A short implementation of bandit algorithms - ETC, UCB, MOSS and KL-UCB
This project focuses on comparing different Reinforcement Learning Algorithms, including monte-carlo, q-learning, lambda q-learning epsilon-greedy variations, etc.
This is an implementation of the Reinforcement Learning multi-arm-bandit experiment using different exploration techniques.
Repository Containing Comparison of two methods for dealing with Exploration-Exploitation dilemma for MultiArmed Bandits
over-parameterization = exploration ?
Classic papers and resources on recommendation
Research Thesis - Reinforcement Learning
This is the pytorch implementation of ICML 2018 paper - Self-Imitation Learning.
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