PyPI Stats
  • Insights
  • PyPI
  • GitHub
  • Search
  • Compare
  • Advisories
  • Ecosystem
  • About
Home

Search Packages

Find Python packages by name, description, GitHub topic, or filter by metrics
pytorch
torchrl

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

1.3M 3K 450
Farama-Foundation
pettingzoo

An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities

338K 3K 484
pytorch
torchrl-nightly

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

37K 3K 450
yamoling
laser-learning-environment

The Laser Learning Environment (LLE) is a cooperative MARL grid-world

31K 13 6
zombie-einstein
esquilax

JAX Multi-Agent RL, Neuro-Evolution, and A-Life Library

8K 14 0
pfeinsper
dsse

The Drone Swarm Search project provides an environment for SAR missions built on PettingZoo, where agents, represented by drones, are tasked with locating targets identified as shipwrecked individuals.

4K 72 14
proroklab
vmas

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

4K 563 107
semitable
rware

Multi-Robot Warehouse (RWARE): A multi-agent reinforcement learning environment

3K 428 95
microsoft
pymaro

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

3K 914 157
flatland-association
flatland-rl

The Flatland Framework is a multi-purpose environment to tackle problems around resilient resource allocation under uncertainty. It is designed to be a flexible and method agnostic to solve a wide range of problems in the field of operations research and reinforcement learning.

3K 63 18
chimera0
accelbrainbeat

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

2K 325 91
chimera0
pydbm

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

2K 325 91
instadeepai
matrax

A collection of matrix games in JAX

2K 13 2
accel-brain
pysummarization

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

1K 325 91
agi-brain
xuance

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

1K 1K 156
chatarena
chatarena

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

1K 2K 147
accel-brain
pyqlearning

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

983 325 91
OpenRL-Lab
openrl

unified reinforcement learning framework

895 829 81
facebookresearch
benchmarl

BenchMARL is a library for benchmarking Multi-Agent Reinforcement Learning (MARL). BenchMARL allows to quickly compare different MARL algorithms, tasks, and models while being systematically grounded in its two core tenets: reproducibility and standardization.

837 617 128
salesforce
ai-economist

Foundation: An Economics Simulation Framework

820 106 28
stefanbschneider
mobile-env

An open, minimalist Gymnasium environment for autonomous coordination in wireless mobile networks.

636 152 31
CN-UPB
deepcomp

DeepCoMP: Self-Learning Dynamic Multi-Cell Selection for Coordinated Multipoint (CoMP)

629 66 13
COeXISTENCE-PROJECT
routerlurb

RouteRL is a multi-agent reinforcement learning framework for urban route choice in different city networks. This subpackage is developed to support its compatibility with URB until the full integration.

625 40 13
accel-brain
accel-brain-base

accel-brain-base is a basic library of the Deep Learning for rapid development at low cost. This library makes it possible to design and implement deep learning, which must be configured as a complex system, by combining a plurality of functionally differentiated modules such as a Deep Boltzmann Machines(DBMs), an Auto-Encoder, an Encoder/Decoder based on Long Short-Term Memory(LSTM), a Convolutional Auto-Encoder(CAE), and Transformer.

584 325 91
    • Data from PyPI, GitHub, ClickHouse, and BigQuery