XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning
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Updated
Jun 19, 2024 - Python
XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning
Reading list for adversarial perspective and robustness in deep reinforcement learning.
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
📚 List of Top-tier Conference Papers on Reinforcement Learning (RL),including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.
Related papers for reinforcement learning, including classic papers and latest papers in top conferences
JAX-accelerated Meta-Reinforcement Learning Environments Inspired by XLand and MiniGrid 🏎️
Code for the "Evolving Reservoirs for Meta Reinforcement Learning" paper
A collection of Meta-Reinforcement Learning algorithms in PyTorch
🎉🎨 This repository contains a reading list of papers with code on **Meta-Learning** and ***Meta-Reinforcement-Learning*
A Survey Analyzing Generalization in Deep Reinforcement Learning
The proceedings of top conference in 2017 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
The proceedings of top conference in 2018 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
The proceedings of top conference in 2019 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
The proceedings of top conference in 2020 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
The proceedings of top conference in 2021 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
The proceedings of top conference in 2023 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
Implementation of the paper "MERINA+: Improving Generalization for Neural Video Adaptation via Information-Theoretic Meta-Reinforcement Learning" - N. Kan, et. al., 2023
Code snippets of Meta Reinforcement Learning algorithms
Python code to implement hard sampling based task representation learning for robust offline meta RL
Implementation of Improving Generalization for Neural Adaptive Video Streaming via Meta Reinforcement Learning - N. Kan et al. (ACM MM22)
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