Explore our product documentation and see how Pathmind is used in simulation models across industries.


Pathmind Tutorial Models

Getting Started

Introducing Pathmind and the basics of reinforcement learning with a simple stochastic model.


Finding the Cheese

Getting to know Pathmind with a simple mouse and cheese model.

Moon Landing

Landing a lunar module safely on the moon while considering speed, distance from target, and fuel consumption.

Coffee Shop

Balancing customer wait times with kitchen cleanliness in a coffee shop operation.

Bass Diffusion Marketing Model

Adapting a simple Bass Diffusion Model for AI success and comparing reinforcement learning to a baseline optimizer.

Interconnected Call Centers

Using AI to optimize call routing in a network of interconnected call centers.

Automated Guided Vehicle (AGV)

Coordinating a fleet of AGVs in a factory to maximize product throughput.

Supply Chain Optimization

Comparing reinforcement learning and an optimizer to manage inventory levels in a supply chain model.

Warehouse Delivery

Determining which factories should to deliver to which warehouses for maximum efficiency and profitability.

Simple Product Delivery

Routing deliveries from manufacturers to distributors while maximizing profit and minimizing wait times.

Multi-Echelon Product Delivery

Determining where to order more inventory from and how much to order in a multi-echelon supply chain.

Help Documents


Pathmind Helper

Instructions for setting up the Pathmind Helper and adding reinforcement learning functions to a model.

Pathmind Features

Resources for understanding the Pathmind Training web application and training mechanics.


Answers to some commonly-asked questions about reinforcement learning terms and using Pathmind.

Pathmind Helper

Download the Pathmind Helper and begin adding reinforcement learning functions to simulation models.


Agent-Based Modeling and Reinforcement Learning for Optimizing Energy Systems Operations and Maintenance: The Pathmind Solution | Read

Dynamically Changing Sequencing Rules with Reinforcement Learning in a Job Shop System with Stochastic Influences | Read

Outperformed by a Computer? Comparing Human Decisions to Reinforcement Learning Agents, Assigning Lot Sizes in a Learning Factory | Read

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