TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
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Updated
Oct 6, 2025 - Python
TorchOpt is an efficient library for differentiable optimization built upon PyTorch.
Related papers for reinforcement learning, including classic papers and latest papers in top conferences
📚 List of Top-tier Conference Papers on Reinforcement Learning (RL),including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.
JAX-accelerated Meta-Reinforcement Learning Environments Inspired by XLand and MiniGrid 🏎️
XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning - - — ICLR 2025
Implementation of 'RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning'
Implementation of the two-step-task as described in "Prefrontal cortex as a meta-reinforcement learning system" and "Learning to Reinforcement Learn".
A collection of Meta-Reinforcement Learning algorithms in PyTorch
🎉🎨 Papers, CODE, Datasets for Meta-Learning and Meta-Reinforcement-Learning
Code snippets of Meta Reinforcement Learning algorithms
PyTorch implementation of Episodic Meta Reinforcement Learning on variants of the "Two-Step" task. Reproduces the results found in three papers. Check the ReadMe for more details!
Code for paper "Model-based Adversarial Meta-Reinforcement Learning" (https://arxiv.org/abs/2006.08875)
A Survey Analyzing Generalization in Deep Reinforcement Learning
Implementation of Improving Generalization for Neural Adaptive Video Streaming via Meta Reinforcement Learning - N. Kan et al. (ACM MM22)
The proceedings of top conference in 2023 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
Next-gen Foundation Model for Embodied AI
Patent : An anti-jamming communication method for unmanned cluster based on meta-reinforcement learning (一种基于元强化学习的无人集群抗干扰通信方法)
Xenoverse is a collection of randomized RL, Language, and general-purpose simulation environments, designed for training General-Purpose Learning Agents (GLAs).
a novel algo for meta-MARL; 元-多智能体强化学习算法
PyTorch implementation of two variants of the Harlow visual fixation task (PsychLab and 1D version). Reproduces the results found in two papers. Check the ReadMe for more details!
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