Pytorch code for ICLR-20 Paper "Learning to Explore using Active Neural SLAM"
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Updated
Jun 17, 2024 - Python
Pytorch code for ICLR-20 Paper "Learning to Explore using Active Neural SLAM"
CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
Pytorch code for NeurIPS-20 Paper "Object Goal Navigation using Goal-Oriented Semantic Exploration"
✨ A plotter for reinforcement learning (RL)
Codes accompanying the paper "Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning" (NeurIPS 2021 Spotlight https://arxiv.org/abs/2106.03400)
Recall to Imagine, a model-based RL algorithm with superhuman memory. Oral (1.2%) @ ICLR 2024
Accelerated minigrid environments with JAX
Mirror Descent Policy Optimization
A general model-free off-policy actor-critic implementation. Continuous and Discrete Soft Actor-Critic with multimodal observations, data augmentation, offline learning and behavioral cloning.
OpenAI团队的深度强化学习教程中文版
Deep Reinforcement Learning framework based on TensorFlow and OpenAI Gym
This repository implements the use of AI for robot tasks.
RLbox: Solving OpenAI Gym with TensorFlow
Code for NeurIPS 2023 paper Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples
Exploration of deep reinforcement learning and various state-of-the-art techniques to create a turely autonomous agent.
Yet another deep reinforcement learning
My solution to the NeurIPS challenge Learn to Move: Walk Around
Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement Learning
Deep Q-Learning algorithms to solve LunarLander-v2.
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