8.2.1. MLPro-GT-Native - Native Games
Here is a concise series designed to introduce all users to MLPro-GT-Native practically, whether you are new to it or an experienced MLPro user.
No experience with MLPro? To learn more about MLPro, please refer to the Getting Started page of MLPro.
By following the step-by-step guidelines below, we expect you to gain a practical understanding of MLPro-GT and begin using MLPro-GT-Native.
- 1. What is Game Theory?
Game theory is a branch of mathematics and social science that examines strategic interactions among rational decision-makers. It involves modeling scenarios where individuals or entities, referred to as players, make decisions that influence one another. Players choose from a set of strategies, and the resulting outcomes, or payoffs, are determined by the collective decisions. The concept of Nash equilibrium, where no player has an incentive to unilaterally deviate from their chosen strategy, is central to game theory. This framework is widely applied across disciplines such as economics, engineering, political science, and biology, offering insights into strategic decision-making, predicting outcomes, and formulating optimal strategies in interactive situations.
- 2. What is MLPro-GT?
We assume you have a basic understanding of MLPro and game theory. Therefore, you should familiarize yourself with the overview of MLPro-GT by following these steps:
- 3. Understanding Players, Strategies, Payoffs, and Games in MLPro-GT-Native
Our documentation page provides definitions for each main component of game theory, along with instructions on how to set up each component. For a better understanding, you can refer to the following pages:
- 4. Access HowTo Files related to MLPro-GT-Native
For a better understanding of the applications, please refer to our sample applications on the following page: