Pokémon Go as Social Patrol Game:
Pokemon Go has several features. But if the game is simplified in a way, I think it can be regarded as social patrol game.
In the game, players take order of where to go with geological signals, such as PokeStops, Gyms, and animation of grass that is a pokemon’s spot.
Then players go to the spot and take picture.
It is a basic flow of Pokemon Go. It is patrol of city by players, controlled by the game.
Reversed version of Metal Gear Solid:
It can be regarded as social patrol game as well. And It is a reversed version of Metal Gear Solid — or Metal Gear Go?.
In Metal Gear Solid, a player tries not to be found by enemy soldiers (genome soldiers) who patrol potential routes of intruder.
In Pokemon Go, inversely, a player patrols real routes of cities, to find pokemons.
The game designs are opposite each other.
Social Patrol Game:
The game can control player’s activity in a city at will, by setting timing and location of appearance of pokemons.
For the game architect, obviously it can be used to make crowd at a location.
But one of other usages is to make players patrol around a region. It is useful to detect crime or incident in a region, the same way as patrol can do.
Pokemon Go’s accomplishments or incidents as patrol already happened in reality.
For example, a player found a dead body during playing the game (The top five most surprising stories about Pokémon Go … so far | Technology | The Guardian).
So I regard the game as social patrol game in the blog post.
Central Active Area:
It is a player’s main active area where the player frequently searches. The center is usually player’s home, and area is the neighborhood.
Size of area depends on players.
The data would be like (location, radius size).
Central Active Time:
It is similar to player’s area. It’s specific time-duration of player’s activity.
The data would be like (start time, end time).
It is amount of player’s reaction by reward, such as getting pokemons, dominating gyms, or getting items.
Players who have high Reward Sensibility in the game are more getting into the game than usual players.
Rare Pokemon Sensibility:
If you see the game as patrol game, a spot where a rare pokemon appears is indication of more important spot than other spots.
It is similar functionality as gain or weight in machine learning or AI. The more weighted route has to be searched faster or intensively in search problems.
Players who have high Rare Pokemon Sensibility are good patrol robot in this regard.
Efficiency Metrics of Patrol:
If you think Pokemon Go as patrol game, it is less efficient when many players on a spot at the same time.
Ideally one player should walk a route and take picture of a spot in a time. And no duplication should be there.
So how to distribute players around area and time is primary goal for the game architect.
Changing spot and species of pokemon is a good way for the purpose.
Here, rather than proposing the method, I made metrics of patrol efficiency to verify the effect of changes.
Patrol Coverage Rate:
This is basic metric of patrol.
It is ratio of whole area and time versus patrolled area and time.
Player as Resource:
Using the player model above, Player’s activity is fundamental resource of patrol.
The game architect confronts limitation of patrol resource based on player’s area, time, reward sensibility, and rare pokemon sensibility.
But limitation of resource can be changed when game design is changed. So the player model is a metric of patrol efficiency .
Pokemon Go can be a social patrol game. It is also seen as social engineering game by companies.
The game is not always nice tool because it shows ability that companies can manipulate people’s real-life action by a game.
But if the tool is used by proper control, it is a good gadget for patrol, then keep security for regions.