Effectiveness of greedily collecting items in open world games

TL;DR

This paper evaluates the effectiveness of a greedy strategy for collecting items in open-world games, showing it performs close to optimal even with human measurement errors, thus validating its practical use.

Contribution

It demonstrates that a simple greedy approach is nearly optimal for item collection in open-world games, accounting for human measurement inaccuracies.

Findings

Greedy collection strategy is only 7% worse than optimal.

Performance degrades to 16% worse with human measurement errors.

The strategy is practical and effective for real-world gameplay scenarios.

Abstract

Since Pokemon Go sent millions on the quest of collecting virtual monsters, an important question has been on the minds of many people: Is going after the closest item first a time-and-cost-effective way to play? Here, we show that this is in fact a good strategy which performs on average only 7% worse than the best possible solution in terms of the total distance traveled to gather all the items. Even when accounting for errors due to the inability of people to accurately measure distances by eye, the performance only goes down to 16% of the optimal solution.