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Level-based Foraging (LBF): A multi-agent environment for RL
Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch
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本书为《C++17 the complete guide》的个人中文翻译，仅供学习和交流使用，侵删
[NeurIPS 2021] Official implementation of paper "Learning to Simulate Self-driven Particles System with Coordinated Policy Optimization".
Collection of reinforcement learning algorithms
FedFormer: Contextual Federation with Attention in Reinforcement Learning (AAMAS 2023)
Deep Deterministic Policy Gradient (DDPG) in Tensorflow 2
A PyTorch implementation of the Transformer model in "Attention is All You Need".
This project uses a variety of advanced voiceprint recognition models such as EcapaTdnn, ResNetSE, ERes2Net, CAM++, etc. It is not excluded that more models will be supported in the future. At the …
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
source code to ICLR'19, 'A Closer Look at Few-shot Classification'
Official source code to CVPR'20 paper, "When2com: Multi-Agent Perception via Communication Graph Grouping"
Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
multi-agent deep reinforcement learning for networked system control.
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
Codes accompanying the paper "Learning Nearly Decomposable Value Functions with Communication Minimization" (ICLR 2020)
pytorch implementation of "Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control"
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.