<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Agent-Based-Model on TouchingFish.top</title><link>https://touchingfish.top/en/tags/agent-based-model/</link><description>Recent content in Agent-Based-Model on TouchingFish.top</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 04 Feb 2023 00:00:00 +0000</lastBuildDate><atom:link href="https://touchingfish.top/en/tags/agent-based-model/index.xml" rel="self" type="application/rss+xml"/><item><title>The Velocity and Inertia of Evolution</title><link>https://touchingfish.top/en/2023/evolutionary-game-dynamic/</link><pubDate>Sat, 04 Feb 2023 00:00:00 +0000</pubDate><guid>https://touchingfish.top/en/2023/evolutionary-game-dynamic/</guid><description>&lt;p&gt;I do not know the mathematics of evolutionary games, and Replicator Dynamics is just a name to me. But I do know how to run computer simulations, and the Agent-Based Model (ABM) is my language.&lt;/p&gt;
&lt;p&gt;Suppose we have an $n \times n$ grid. Generate a population of agents by multiplying the number of cells by the population density. At each step, agents carry an action, move across the grid, find another agent in their Von Neumann neighbourhood, play a round of a classical game, then update their action and move to the next step. All agents update their action the same way. The above defines the basic elements of the model.&lt;/p&gt;</description></item></channel></rss>