[ICML 2020] Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control

Kalman Filter, Smoother, and EM Algorithm for Python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

This is a Kalman filter used to calculate the angle, rate and bias from from the input of an accelerometer/magnetometer and a gyroscope.

Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoo…

Model predictive control python toolbox

Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code

Distributed Evolutionary Algorithms in Python

NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO

Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

Modularized Implementation of Deep RL Algorithms in PyTorch

Massively Parallel Deep Reinforcement Learning. 🔥

Reinforcement learning resources curated

The Robotics Library (RL) is a self-contained C++ library for rigid body kinematics and dynamics, motion planning, and control.

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

Implementation of several multiagent trajectory generation algorithms

The multi-agent version of TORCS for developing control algorithms for fully autonomous driving in the cluttered, multi-agent settings of everyday life.

The Multiagent Decision Process (MADP) Toolbox - planning and learning in multiagent systems.

Code for the paper "Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents"

Benchmark for Continuous Multi-Agent Robotic Control, based on OpenAI's Mujoco Gym environments.

Langflow is a powerful tool for building and deploying AI-powered agents and workflows.

OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.

Code for the paper "Emergent Complexity via Multi-agent Competition"

LLM-powered multiagent persona simulation for imagination enhancement and business insights.

Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

Powerful convenience for Julia visualizations and data analysis

Tutorials and information on the Julia language for MIT numerical-computation courses.

Interactive data visualizations and plotting in Julia

A Julia machine learning framework