Examples¶
This gallery contains examples demonstrating the functionality of scikit-agent. The examples are organized by topic and show how to use the various modules and classes in practical scenarios.
Each example is designed to be self-contained and can be run independently. The examples demonstrate real-world usage patterns and best practices for using scikit-agent in your research and applications.
Algorithms¶
This section contains examples of different algorithms available in scikit-agent. These examples demonstrate how to use various solution methods, optimization algorithms, and numerical techniques.
Examples include value function iteration, policy iteration, neural network training, and other computational approaches to solving economic models.
Economic Models¶
This section contains examples demonstrating how to use and create economic models with scikit-agent. These examples show how to implement various economic theories and models using the framework.
Examples include consumption-savings models, portfolio choice problems, and other standard economic models that can be solved using reinforcement learning and other computational methods.
Simulation Examples¶
This section demonstrates how to run simulations using scikit-agent models. These examples show how to generate synthetic data, run Monte Carlo simulations, and analyze the results.
Examples include life-cycle simulations, policy experiments, and sensitivity analyses that help understand model behavior under different conditions.