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of all others. This keeps the schedules desynchronized, and motivation
emeRgent ReinfoRCement sCHeDules
So far we've looked at explicitly designed reinforcement schedules.
Designers build these schedules like Skinner built his boxes, deciding
with mathematical precision exactly what the player will get after each
action. But this kind of explicitly defined reinforcement schedule is the
exception, not the rule.
Most reinforcement schedules are not designed directly. Rather, they
emerge from lower-level game systems.
For example, in chess, a player will tend to capture a piece every X
minutes. This isn't because a designer set the variable X . Rather, the in-
terval X emerges naturally from the interaction of the lower-level mechan-
ics of the game. In chess, the pacing of captures is very spiky—players
construct interlocking defensive positions over many minutes, and then
destroy them in a flurry of captures. Since that exchange could happen on
any turn, chess emergently presents a variable ratio reward schedule. And
if the rules changed, so would this schedule.
Players respond to emergent reward schedules the same way they re-
spond to explicitly defined ones. Often, they're the difference between a
game that grabs you and one that lets you drift away.
For example, many shooters have a multiplayer deathmatch mode.
The goal of a deathmatch is to kill as many other players as possible. At the
end of the match, the players are shown their kill count. This kill count is
a reward, because it feels good to get a high kill count and bad to get a low
one. In the language of rewards, each match is like a defeated orc, except
that it spits out kills instead of money. But whereas the orc's gold drops
are determined by an algorithm, the kill count emerges from the game's
combat design. Different map layouts, weapon tunings, and matchmaking
systems produce different patterns of kill counts.
In some deathmatch games, kill counts are very consistent. A good
player always gets many kills, while a poor player always gets few kills.
This produces an emergent reinforcement schedule that resembles a fixed
ratio. Like all fixed ratio schedules, it creates a motivation gap right after
getting the reward (i.e., right after finishing a match). After a match ends,
players aren't compelled to start a new one because they know exactly
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