126 Repositories
Python checkmk-agent Libraries
A platform for intelligent agent learning based on a 3D open-world FPS game developed by Inspir.AI.
Wilderness Scavenger: 3D Open-World FPS Game AI Challenge This is a platform for intelligent agent learning based on a 3D open-world FPS game develope
[ICRA 2022] An opensource framework for cooperative detection. Official implementation for OPV2V.
OpenCOOD OpenCOOD is an Open COOperative Detection framework for autonomous driving. It is also the official implementation of the ICRA 2022 paper OPV
Trajectory Variational Autoencder baseline for Multi-Agent Behavior challenge 2022
MABe_2022_TVAE: a Trajectory Variational Autoencoder baseline for the 2022 Multi-Agent Behavior challenge This repository contains jupyter notebooks t
Download & Install mods for your favorit game with a few simple clicks
Husko's SteamWorkshop Downloader 🔴 IMPORTANT ❗ 🔴 The Tool is currently being rewritten so updates will be slow and only on the dev branch until it i
API for RL algorithm design & testing of BCA (Building Control Agent) HVAC on EnergyPlus building energy simulator by wrapping their EMS Python API
RL - EmsPy (work In Progress...) The EmsPy Python package was made to facilitate Reinforcement Learning (RL) algorithm research for developing and tes
Fake-user-agent-traffic-geneator - Python CLI Tool to generate fake traffic against URLs with configurable user-agents
Fake traffic generator for Gartner Demo Generate fake traffic to URLs with custo
JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces
JAXMAPP: JAX-based Library for Multi-Agent Path Planning in Continuous Spaces JAXMAPP is a JAX-based library for multi-agent path planning (MAPP) in c
PICO is an algorithm for exploiting Reinforcement Learning (RL) on Multi-agent Path Finding tasks.
PICO is an algorithm for exploiting Reinforcement Learning (RL) on Multi-agent Path Finding tasks. It is developed by the Multi-Agent Artificial Intel
Deep Learning agent of Starcraft2, similar to AlphaStar of DeepMind except size of network.
Introduction This repository is for Deep Learning agent of Starcraft2. It is very similar to AlphaStar of DeepMind except size of network. I only test
The mini-AlphaStar (mini-AS, or mAS) - mini-scale version (non-official) of the AlphaStar (AS)
A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II.
PressurePlate is a multi-agent environment that requires agents to cooperate during the traversal of a gridworld.
PressurePlate is a multi-agent environment that requires agents to cooperate during the traversal of a gridworld. The grid is partitioned into several rooms, and each room contains a plate and a closed doorway.
Checkmk kube agent - Checkmk Kubernetes Cluster and Node Collectors
Checkmk Kubernetes Cluster and Node Collectors Checkmk cluster and node collecto
An evolutionary multi-agent platform based on mesa and NEAT
An evolutionary multi-agent platform based on mesa and NEAT
TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments for IV 2022.
TorchGRL TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffi
This is an implementation example of a bot that periodically sends predictions to the alphasea-agent.
alphasea-example-model alphasea-example-modelは、 alphasea-agent に対して毎ラウンド、予測を投稿するプログラムです。 Numeraiのexample modelに相当します。 準備 alphasea-example-modelの動作には、
CTRMs: Learning to Construct Cooperative Timed Roadmaps for Multi-agent Path Planning in Continuous Spaces
CTRMs: Learning to Construct Cooperative Timed Roadmaps for Multi-agent Path Planning in Continuous Spaces This is a repository for the following pape
An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available actions
Agar.io_Q-Learning_AI An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available act
MADT: Offline Pre-trained Multi-Agent Decision Transformer
MADT: Offline Pre-trained Multi-Agent Decision Transformer A link to our paper can be found on Arxiv. Overview Official codebase for Offline Pre-train
Gym for multi-agent reinforcement learning
PettingZoo is a Python library for conducting research in multi-agent reinforcement learning, akin to a multi-agent version of Gym. Our website, with
Python Multi-Agent Reinforcement Learning framework
- Please pay attention to the version of SC2 you are using for your experiments. - Performance is *not* always comparable between versions. - The re
A2DP agent for promiscuous/permissive audio sinc.
Promiscuous Bluetooth audio sinc A2DP agent for promiscuous/permissive audio sinc for Linux. Once installed, a Bluetooth client, such as a smart phone
Official PyTorch Implementation of "AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting".
AgentFormer This repo contains the official implementation of our paper: AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecast
Multi-task Multi-agent Soft Actor Critic for SMAC
Multi-task Multi-agent Soft Actor Critic for SMAC Overview The CARE formulti-task: Multi-Task Reinforcement Learning with Context-based Representation
Code corresponding to The Introspective Agent: Interdependence of Strategy, Physiology, and Sensing for Embodied Agents
The Introspective Agent: Interdependence of Strategy, Physiology, and Sensing for Embodied Agents This is the code corresponding to The Introspective
Pytorch implementations of the paper Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients
LSF-SAC Pytorch implementations of the paper Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy G
CVE-log4j CheckMK plugin
CVE-2021-44228-log4j discovery (Download the MKP package) This plugin discovers vulnerable files for the CVE-2021-44228-log4j issue. To discover this
Pacman-AI - AI project designed by UC Berkeley. Designed reflex and minimax agents for the game Pacman.
Pacman AI Jussi Doherty CAP 4601 - Introduction to Artificial Intelligence - Fall 2020 Python version 3.0+ Source of this project This repo contains a
Covid-ChatBot - A Rapid Response Virtual Agent for Covid-19 Queries
COVID-19 CHatBot A Rapid Response Virtual Agent for Covid-19 Queries Contents What is ChatBot Types of ChatBots About the Project Dataset Prerequisite
Multi agent DDPG algorithm written in Python + Pytorch
Multi agent DDPG algorithm written in Python + Pytorch. It also includes a Jupyter notebook, Tennis.ipynb, as a showcase.
Coerce authentication from Windows hosts via MS-FSRVP (Requires FS-VSS-AGENT service running on host)
VSSTrigger Coerce authentication from Windows hosts via MS-FSRVP (Requires FS-VS
ScoutAPM Python Agent. Supports Django, Flask, and many other frameworks.
Scout Python APM Agent Monitor the performance of Python Django apps, Flask apps, and Celery workers with Scout's Python APM Agent. Detailed performan
PyDynamica is a freely available agent-based economy simulation
PyDynamica PyDynamica is a pure python implementation of Sociodynamica, a virtual environment to simulate a simple economy with minimal dependencies.
A modern message based async agent framework
Munggoggo A modern message based async agent framework An asyncio based agent platform written in Python and based on RabbitMQ. Agents are isolated pr
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning
Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning This is the code for implementing the MADDPG algorithm presented in
Minecraft agent to farm resources using reinforcement learning
BarnyardBot CS 175 group project using Malmo download BarnyardBot.py into the python examples directory and run 'python BarnyardBot.py' in the console
RL agent to play μRTS with Stable-Baselines3
Gym-μRTS with Stable-Baselines3/PyTorch This repo contains an attempt to reproduce Gridnet PPO with invalid action masking algorithm to play μRTS usin
Pytorch modules for paralel models with same architecture. Ideal for multi agent-based systems
WideLinears Pytorch parallel Neural Networks A package of pytorch modules for fast paralellization of separate deep neural networks. Ideal for agent-b
Offline Multi-Agent Reinforcement Learning Implementations: Solving Overcooked Game with Data-Driven Method
Overcooked-AI We suppose to apply traditional offline reinforcement learning technique to multi-agent algorithm. In this repository, we implemented be
Scans for Log4j versions effected by CVE-2021-44228
check_mkExtension to check for log4j2 CVE-2021-44228 This Plugin wraps around logpresso/CVE-2021-44228-Scanner (Apache License 2.0) How it works Run i
PantheonRL is a package for training and testing multi-agent reinforcement learning environments.
PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.
A python interface for training Reinforcement Learning bots to battle on pokemon showdown
The pokemon showdown Python environment A Python interface to create battling pokemon agents. poke-env offers an easy-to-use interface for creating ru
Python HTTP Agent Parser
Features Fast Detects OS and Browser. Does not aim to be a full featured agent parser Will not turn into django-httpagentparser ;) Usage import ht
A simple agent-based model used to teach the basics of OOP in my lectures
Pydemic A simple agent-based model of a pandemic. This is used to teach basic principles of object-oriented programming to master students. It is not
Official Python agent for the Elastic APM
elastic-apm -- Elastic APM agent for Python This is the official Python module for Elastic APM. It provides full out-of-the-box support for many of th
Codebase for the solution that won first place and was awarded the most human-like agent in the 2021 NeurIPS Competition MineRL BASALT Challenge.
KAIROS MineRL BASALT Codebase for the solution that won first place and was awarded the most human-like agent in the 2021 NeurIPS Competition MineRL B
Multi-agent reinforcement learning algorithm and environment
Multi-agent reinforcement learning algorithm and environment [en/cn] Pytorch implements multi-agent reinforcement learning algorithms including IQL, Q
OpenDILab Multi-Agent Environment
Go-Bigger: Multi-Agent Decision Intelligence Environment GoBigger Doc (中文版) Ongoing 2021.11.13 We are holding a competition —— Go-Bigger: Multi-Agent
An audnexus client, providing rich author and audiobook data to Plex via it's legacy plugin agent system.
Audnexus.bundle An audnex.us client, providing rich author and audiobook data to Plex via it's legacy plugin agent system. 📝 Table of Contents About
Cooperative Driving Dataset: a dataset for multi-agent driving scenarios
Cooperative Driving Dataset (CODD) The Cooperative Driving dataset is a synthetic dataset generated using CARLA that contains lidar data from multiple
Scalable Multi-Agent Reinforcement Learning
Scalable Multi-Agent Reinforcement Learning 1. Featured algorithms: Value Function Factorization with Variable Agent Sub-Teams (VAST) [1] 2. Implement
Sample Code for "Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL"
Sample Code for "Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL" This is the official codebase for Pessimism Meets I
Multi Agent Reinforcement Learning for ROS in 2D Simulation Environments
IROS21 information To test the code and reproduce the experiments, follow the installation steps in Installation.md. Afterwards, follow the steps in E
PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems
PowerGridworld provides users with a lightweight, modular, and customizable framework for creating power-systems-focused, multi-agent Gym environments that readily integrate with existing training frameworks for reinforcement learning (RL).
Multi-Agent Reinforcement Learning (MARL) method to learn scalable control polices for multi-agent target tracking.
scalableMARL Scalable Reinforcement Learning Policies for Multi-Agent Control CD. Hsu, H. Jeong, GJ. Pappas, P. Chaudhari. "Scalable Reinforcement Lea
Implementation of MA-Trace - a general-purpose multi-agent RL algorithm for cooperative environments.
Off-Policy Correction For Multi-Agent Reinforcement Learning This repository is the official implementation of Off-Policy Correction For Multi-Agent R
The learning agent learns firstly approaching to the football and then kicking the football to the target position
Football Court This project utilized Pytorch and Tensorflow so that the learning agent learns firstly approaching to the football and then kicking the
Cooperative multi-agent reinforcement learning for high-dimensional nonequilibrium control
Cooperative multi-agent reinforcement learning for high-dimensional nonequilibrium control Official implementation of: Cooperative multi-agent reinfor
Python script to check if there is any differences in responses of an application when the request comes from a search engine's crawler.
crawlersuseragents This Python script can be used to check if there is any differences in responses of an application when the request comes from a se
The Python agent for Apache SkyWalking
SkyWalking Python Agent SkyWalking-Python: The Python Agent for Apache SkyWalking, which provides the native tracing abilities for Python project. Sky
Codes accompanying the paper "Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning" (NeurIPS 2021 Spotlight
Implicit Constraint Q-Learning This is a pytorch implementation of ICQ on Datasets for Deep Data-Driven Reinforcement Learning (D4RL) and ICQ-MA on SM
CityLearn Challenge Multi-Agent Reinforcement Learning for Intelligent Energy Management, 2020, PikaPika team
Citylearn Challenge This is the PyTorch implementation for PikaPika team, CityLearn Challenge Multi-Agent Reinforcement Learning for Intelligent Energ
[ICCV21] Official implementation of the "Social NCE: Contrastive Learning of Socially-aware Motion Representations" in PyTorch.
Social-NCE + CrowdNav Website | Paper | Video | Social NCE + Trajectron | Social NCE + STGCNN This is an official implementation for Social NCE: Contr
Trains an agent with stochastic policy gradient ascent to solve the Lunar Lander challenge from OpenAI
Introduction This script trains an agent with stochastic policy gradient ascent to solve the Lunar Lander challenge from OpenAI. In order to run this
Learning-based agent for Google Research Football
TiKick 1.Introduction Learning-based agent for Google Research Football Code accompanying the paper "TiKick: Towards Playing Multi-agent Football Full
Python implementation of Lightning-rod Agent, the Stack4Things board-side probe
Iotronic Lightning-rod Agent Python implementation of Lightning-rod Agent, the Stack4Things board-side probe. Free software: Apache 2.0 license Websit
Agent-based model simulator for air quality and pandemic risk assessment in architectural spaces
Agent-based model simulation for air quality and pandemic risk assessment in architectural spaces. User Guide archABM is a fast and open source agent-
DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021]
DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021] Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng
A software dedicated to automaticaly select the agent of your desire in Valorant
AUTOPICKER A software dedicated to automaticaly select the agent of your desire in Valorant GUIDE Before stariting to use this program check if you ha
Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks (MAPDN)
Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks (MAPDN) This is the implementation of the paper Multi-Age
[NeurIPS 2021] Official implementation of paper "Learning to Simulate Self-driven Particles System with Coordinated Policy Optimization".
Code for Coordinated Policy Optimization Webpage | Code | Paper | Talk (English) | Talk (Chinese) Hi there! This is the source code of the paper “Lear
This code uses generative adversarial networks to generate diverse task allocation plans for Multi-agent teams.
Mutli-agent task allocation This code uses generative adversarial networks to generate diverse task allocation plans for Multi-agent teams. To change
A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.
AMAZ3DSim AMAZ3DSim is a lightweight python-based 3D network multi-agent simulator. It uses a cell-based congestion model. It calculates risk, battery
Urban mobility simulations with Python3, RLlib (Deep Reinforcement Learning) and Mesa (Agent-based modeling)
Deep Reinforcement Learning for Smart Cities Documentation RLlib: https://docs.ray.io/en/master/rllib.html Mesa: https://mesa.readthedocs.io/en/stable
Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI
Language Emergence in Multi Agent Dialog Code for the Paper Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog Satwik Kottur, José M.
A command line connect 4 game against a minimax agent.
A command line connect 4 game against a minimax agent.
A tensorflow implementation of the RecoGCN model in a CIKM'19 paper, titled with "Relation-Aware Graph Convolutional Networks for Agent-Initiated Social E-Commerce Recommendation".
This repo contains a tensorflow implementation of RecoGCN and the experiment dataset Running the RecoGCN model python train.py Example training outp
Anomaly detection in multi-agent trajectories: Code for training, evaluation and the OpenAI highway simulation.
Anomaly Detection in Multi-Agent Trajectories for Automated Driving This is the official project page including the paper, code, simulation, baseline
Hexagon game. Two players: AI and User. Implemented using Alpha-Beta pruning to find optimal solution for agent.
Hexagon game. Two players: AI and User. Implemented using Alpha-Beta pruning to find optimal solution for agent.
An OpenAI Gym environment for multi-agent car racing based on Gym's original car racing environment.
Multi-Car Racing Gym Environment This repository contains MultiCarRacing-v0 a multiplayer variant of Gym's original CarRacing-v0 environment. This env
Minimalistic Gridworld Environment (MiniGrid)
Minimalistic Gridworld Environment (MiniGrid) There are other gridworld Gym environments out there, but this one is designed to be particularly simple
RL-driven agent playing tic-tac-toe on starknet against challengers.
tictactoe-on-starknet RL-driven agent playing tic-tac-toe on starknet against challengers. GUI reference: https://pythonguides.com/create-a-game-using
COVINS -- A Framework for Collaborative Visual-Inertial SLAM and Multi-Agent 3D Mapping
COVINS -- A Framework for Collaborative Visual-Inertial SLAM and Multi-Agent 3D Mapping Version 1.0 COVINS is an accurate, scalable, and versatile vis
Pytorch implementation of CVPR2020 paper “VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation”
VectorNet Re-implementation This is the unofficial pytorch implementation of CVPR2020 paper "VectorNet: Encoding HD Maps and Agent Dynamics from Vecto
Official Implementation of 'UPDeT: Universal Multi-agent Reinforcement Learning via Policy Decoupling with Transformers' ICLR 2021(spotlight)
UPDeT Official Implementation of UPDeT: Universal Multi-agent Reinforcement Learning via Policy Decoupling with Transformers (ICLR 2021 spotlight) The
Code for Emergent Translation in Multi-Agent Communication
Emergent Translation in Multi-Agent Communication PyTorch implementation of the models described in the paper Emergent Translation in Multi-Agent Comm
Reinforcement learning models in ViZDoom environment
DoomNet DoomNet is a ViZDoom agent trained by reinforcement learning. The agent is a neural network that outputs a probability of actions given only p
WarpDrive: Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU
WarpDrive is a flexible, lightweight, and easy-to-use open-source reinforcement learning (RL) framework that implements end-to-end multi-agent RL on a single GPU (Graphics Processing Unit).
[ICCV'21] Official implementation for the paper Social NCE: Contrastive Learning of Socially-aware Motion Representations
CrowdNav with Social-NCE This is an official implementation for the paper Social NCE: Contrastive Learning of Socially-aware Motion Representations by
Customizable RecSys Simulator for OpenAI Gym
gym-recsys: Customizable RecSys Simulator for OpenAI Gym Installation | How to use | Examples | Citation This package describes an OpenAI Gym interfac
Orthrus is a macOS agent that uses Apple's MDM to backdoor a device using a malicious profile.
Orthrus is a macOS agent that uses Apple's MDM to backdoor a device using a malicious profile. It effectively runs its own MDM server and allows the operator to interface with it using Mythic.
Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI
Language Emergence in Multi Agent Dialog Code for the Paper Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog Satwik Kottur, José M.
Pytorch implementations of popular off-policy multi-agent reinforcement learning algorithms, including QMix, VDN, MADDPG, and MATD3.
Off-Policy Multi-Agent Reinforcement Learning (MARL) Algorithms This repository contains implementations of various off-policy multi-agent reinforceme
Train an RL agent to execute natural language instructions in a 3D Environment (PyTorch)
Gated-Attention Architectures for Task-Oriented Language Grounding This is a PyTorch implementation of the AAAI-18 paper: Gated-Attention Architecture
Code for Emergent Translation in Multi-Agent Communication
Emergent Translation in Multi-Agent Communication PyTorch implementation of the models described in the paper Emergent Translation in Multi-Agent Comm
Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch
Learning to Communicate with Deep Multi-Agent Reinforcement Learning This is a PyTorch implementation of the original Lua code release. Overview This
A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).
GAM ⠀⠀ A PyTorch implementation of Graph Classification Using Structural Attention (KDD 2018). Abstract Graph classification is a problem with practic
Medusa is a cross-platform agent compatible with both Python 3.8 and Python 2.7.
Medusa Medusa is a cross-platform agent compatible with both Python 3.8 and Python 2.7. Installation To install Medusa, you'll need Mythic installed o
Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"
Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr
Artificial Intelligence search algorithm base on Pacman
Pacman Search Artificial Intelligence search algorithm base on Pacman Source The Pacman Projects by the University of California, Berkeley. Layouts Di
A library of multi-agent reinforcement learning components and systems
Mava: a research framework for distributed multi-agent reinforcement learning Table of Contents Overview Getting Started Supported Environments System