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Value-Decomposition Multi-Agent Actor-Critics
My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entr…
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
Graph Attention Networks (https://arxiv.org/abs/1710.10903)
Public implementation of "Multi-Agent Graph-Attention Communication and Teaming" from AAMAS'21
Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch
面向北京码农同胞的从0开始的买房踩盘实录，目标只有一个: 每一分钱都花的明白(持续补充和完善ing…)
The pytorch implementation of DGN on grid world and Starcraft
Implementation code for GraphMIX: Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning
discrete soft Q learning(SQL) and soft Q imitation learning(SQIL) implementation in pytorch, simple!
Pytorch GAIL VAIL AIRL VAIRL EAIRL SQIL Implementation
xingtian is a componentized library for the development and verification of reinforcement learning algorithms
Code for Continual Learning of Context-dependent Processing in Neural Networks
A PyTorch implementation of the ECCV 2018 publication "Memory Aware Synapses: Learning what (not) to forget"
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.
StarCraft II / PySC2 Deep Reinforcement Learning Agents (A2C)
PyTorch implementation of Advantage Actor-Critic (A2C)
A Test-Implementation of the IMPALA algorithm (by deepmind 2018)
SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKT…
This is the official implementation of Multi-Agent PPO (MAPPO).
Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)
This repository is the official implementation of Learning Multi-Agent Coordination for Enhancing Target Coverage in Directional Sensor Networks.
A pytorch implementation of commNet on the levers task from "Learning Multiagent Communication with Backpropagation" paper. Reproduced from https://github.com/facebookarchive/CommNet