Pathmind Web App

Get started with training your policy

15 articles in this collection
Written by Edward, Ryan, and Johnny

Getting Started

Export your AnyLogic simulation to Pathmind via RLExperiment

AnyLogic's RLExperiment provides an easy way to export your AnyLogic simulations to Pathmind.

Written by Edward
Updated over a week ago

[AnyLogic Professional Only] Export your AnyLogic simulation to Pathmind via standalone JAR

Written by Edward
Updated over a week ago

Writing your first reward function

Written by Edward
Updated over a week ago

Interpreting the learning progress graph

Written by Edward
Updated over a week ago

Pathmind Webapp Features

Defining Metric Names

Written by Edward
Updated over a week ago

Simulation Parameters

Written by Edward
Updated over a week ago

Pathmind Experiment Settings

Enable longer trainings and deeper neural networks

Written by Edward
Updated over a week ago

Observation Selection

Dynamically select specific observations for policy training

Written by Edward
Updated over a week ago

Simulation Metrics

Track KPIs as training progresses in real-time

Written by Edward
Updated over a week ago

Policy Evaluation Histograms

How to inspect a policy's expected performance from Pathmind

Written by Edward
Updated over a week ago

Share Experiments Publicly

Written by Ryan
Updated over a week ago

Reward Shaping

Reward Function Syntax

Written by Edward
Updated over a week ago

Reward Functions and Reward Shaping

Learn how to write and shape a reward function

Written by Johnny
Updated over a week ago

Advanced

Pathmind Training Mechanics and Hyperparameter Tuning

Written by Edward
Updated over a week ago

Policy Stochasticity and Policy Freezing

Written by Edward
Updated over a week ago