Cookie Clicker

TL;DR

This paper analyzes optimal strategies for playing Cookie Clicker, an incremental game, using concepts from NP-hardness, approximation algorithms, and dynamic programming to understand its complexity and solution approaches.

Contribution

It introduces a formal analysis of Cookie Clicker's gameplay strategies, applying advanced computational techniques to determine optimal play.

Findings

Game involves NP-hardness considerations

Approximation algorithms can be applied for strategy optimization

Dynamic programming helps in deriving optimal solutions

Abstract

Cookie Clicker is a popular online incremental game where the goal of the game is to generate as many cookies as possible. In the game you start with an initial cookie generation rate, and you can use cookies as currency to purchase various items that increase your cookie generation rate. In this paper, we analyze strategies for playing Cookie Clicker optimally. While simple to state, the game gives rise to interesting analysis involving ideas from NP-hardness, approximation algorithms, and dynamic programming.