📚 List of Top-tier Conference Papers on Reinforcement Learning (RL),including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.
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Updated
May 21, 2024
📚 List of Top-tier Conference Papers on Reinforcement Learning (RL),including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.
An environement builder for hierarchical reasoning research
[AAAI 2024] GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time
Heterogeneous Hierarchical Multi Agent Reinforcement Learning for Air Combat
A Python package that provides a simple framework for working with Options in Reinforcement Learning.
Implementation of STAR from the paper "Reconciling Spatial and Temporal Abstractions for Goal Representation" (ICLR 2024)
For deep RL and the future of AI.
The proceedings of top conference in 2023 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.
PyTorch code accompanying the paper "Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning" (NeurIPS 2020 spotlight).
[NeurIPS 2023] Official code release accompanying the paper "NetHack is Hard to Hack" (Piterbarg, Pinto, Fergus)
A collection of useful environments for testing Reinforcement Learning algorithms. Designed (mostly) with discrete, graph-based methods in mind.
Our codebase trials provide an implementation of the Select and Trade paper, which proposes a new paradigm for pair trading using hierarchical reinforcement learning. It includes the code for the proposed method and experimental results on real-world stock data to demonstrate its effectiveness.
Official implementation of H-TSP (AAAI2023)
Pure-python-based, lightweight 2d-navigation environments.
SynGameZero – Flowsheet Synthesis in a Game environment with Zero Knowledge
An end-to-end differentiable hierarchical reinforcement learning agent based on continuous sub-policy attention.
Official code for "DHRL: A Graph-Based Approach for Long-Horizon and Sparse Hierarchical Reinforcement Learning" (NeurIPS 2022 Oral)
Deep Hierarchical Planning from Pixels
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
This is the source code for HDNO: a hierarchical model for task-oriented dialogue system.
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