OpenDILab Decision AI Engine
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Updated
May 8, 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)
A curated list of awesome exploration RL resources (continually updated)
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
For deep RL and the future of AI.
推荐、广告工业界经典以及最前沿的论文、资料集合/ Must-read Papers on Recommendation System and CTR Prediction
Code for NeurIPS 2022 paper Exploiting Reward Shifting in Value-Based Deep RL
Human and sim. behavioral / small-scale neural data for paper: https://www.biorxiv.org/content/10.1101/2022.10.03.510668v2
Exploitation vs Exploration problem stated as A/B-testing with maximum profit per unit time.
Code to reproduce the experiments in Sample Efficient Reinforcement Learning via Model-Ensemble Exploration and Exploitation (MEEE).
Reinforcement Learning (COMP 579) Project
Python implementations of contextual bandits algorithms
This repository contains a variety of projects related to reinforcement learning, showcasing different approaches to implementing it in various scenarios.
Official implementation of LECO (NeurIPS'22)
Some Key Points from the Deep Learning Tuning Playbook
This project uses Reinforcement Learning to teach an agent to drive by itself and learn from its observations so that it can maximize the reward(180+ lines)
An Optimistic Approach to the Q-Network Error in Actor-Critic Methods
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