Matlab agents

The MATLAB Agentic Toolkit brings trusted MATLAB capabilities to AI agents, making engineering and scientific workflows agent-ready.

OpenMAS is an open source multi-agent simulator based in Matlab for the simulation of decentralized intelligent systems defined by arbitrary behaviours and dynamics.

Yang's PhD work

Dynamic decentralized task allocation algorithms for multi-agent systems using auctions

Robotic Order Fulfillment System Using Kiva-like mobile robots. Conflict-based Search multi-robot path planning.

Neural network-based (NN) Model Predictive Control (MPC) algorithm to control a multi-agent system (MAS) with stochastic communication topology.

A collection of skills for AI agents by Guy on Simulink.

Hierarchical multi-agent systems for multiple UAVs

Multi-Drone based Single Object Tracking with Agent Sharing Network

Implementation of Single-Agent and Multi-Agent Reinforcement Learning Algorithms. MATLAB.

Contract net protocol (CNP algorithm), decentralized market-based protocol for multi-agent multi-task allocation problems over networks with time windows, and priority constraints

Design a control system on Matlab for robots so that they are able to form a defined shape, then Artificial Potential Field method is applied for robots to avoid obstacles

Distributed model predictive control for multi-agent point-to-point transitions.

针对基本的一阶二阶多智能体控制，给出了基本 的Matlab仿真

Develop agent-based traffic management system by model-free reinforcement learning

This repository contains the Matlab source codes (to use in Robotarium platform) of various rendezvous controllers for consensus control in a multi-agent / multi-robot system.

Train a reinforcement learning agent to play a variation of Pong®

A MATLAB program that implements Multi-agent flocking, following a target, avoiding obstacles

Simulate the path planning and trajectory planning of quadrotors/UAVs for multi-agents.

consensus and synchronization algorithms of networked multi agent systems with event triggered communications

We explore the application of deep reinforcement learning in the field of robotic control, the cooperative and competitive behavior of multi-agents in different game types, including RPG and MOBA, cloud infrastructure, and software engineering as well.

异构混合阶多智能体系统编队控制的分布式优化

MATLAB code for the numerical example in ``Event-Triggered Consensus for Multi-Agent Systems with Guaranteed Robustly Positive Minimum Inter-Event Times

D2D communication as a multi-agents system, and power control is achieved by maximizing system capacity while maintaining the requirement of quality of service(QoS) from cellular users.

This is a MATLAB-based reinforcement learning framework that includes the Proximal Policy Optimization (PPO) algorithm and its multi-agent extension (MAPPO). It supports GPU acceleration and parallel computing, making it suitable for research and engineering applications in control systems.

二阶多智能体系统固定时间一致性

MATLAB based implementation of ofrmation control of multi-agent system

​​Build and run AI agents in MATLAB with the MATLAB AI Agent SDK​

This repository represents an implementation of suggested distributed control algorithm for formation control of multi-agent system with distrubance compensation.

具有自适应动态协议的线性多智能体系统的分布式一致性

Codes reproducing paper Jongeun Choi, Songhwai Oh, Roberto Horowitz, Distributed learning and cooperative control for multi-agent systems, Automatica, Volume 45, Issue 12, 2009

Publish MATLAB functions as MCP tools for AI agents using MATLAB Production Server

包括UGV和UAV在内的异构混合阶多智能体系统的一致性

Dijkstra+minimum jerk+ORCA(RVO2)

Simulation of a distributed control algorithm to drive a multi-agent system with a single leader (has knowledge about target locations) to the target positions with collision avoidance.

This project is a pipeline that connects a Matlab simulation (Simulink) to an OpenAI Gym wrapper for PyTorch Reinforcement Learning using the DQN algorithm.

Turn macro intuition into validated Dynare .mod files — a coding agent skill for DSGE modeling.

Python and MATLAB codes for Density-Driven Optimal Control (D2OC) using Optimal Transport and Wasserstein distance, enabling decentralized multi-agent / multi-robot non-uniform area coverage.

Decentralized multi-agent collision avoidance

Photovoltaic control using RL methods.

Agent-ready MATLAB and Simulink skill suite for Codex: batch execution, validation, codegen, simulation, and reproducible research workflows.

MEng Final Year Project - Reinforcement Learned Collision Avoidance