Game Development Reference
In-Depth Information
Cook gives an example of these steps in the skill atom that governs jumping in
Super Mario Bros.
:
1.
Action.
The player presses the A button.
2.
Simulation.
The game moves the player character within its internal model of
the world by applying a jumping force and gravity.
3.
Feedback.
The player character moves, its animation changes, and the game
plays a jumping sound.
4.
Modeling.
The player learns that pressing A allows her to jump.
Skill atoms can depend on previously learned skills. Continuing the
Super
Mario
Bros.
example, the player needs to learn how to jump before she can learn that she
can jump onto platforms or that jumping into a certain block will reveal hidden
objects. Linked skill atoms form chains and trees of related skills that can be repre-
sented as graphs. For example, a small part of the skill tree for
Super
Mario Bros.
is
depicted in
Figure 10.12
.
Two important characteristics of a skill tree are its relative width and depth. If a skill
tree is wide, the player must learn many new skills independently of one another.
If a skill tree is deep, it has long chains of skills that depend on each other. In gen-
eral, it is better to have skill trees that are relatively deep instead of relatively wide,
at least to teach the skills required early in the game. The reason is that the player
can pick up secondary skills (skills that build on other skills in the game) compara-
tively easily as an addition to something she already knows, whereas primary skills
(skills at the beginning of the chain) must be learned explicitly without the benefit
of any prior experience. For example, when encountering a new and unfamiliar type
of game, the player has two ways of finding out what the primary skills are: She can
look for in-game instructions, or she can simply try random buttons or other avail-
able input devices. When she has learned a few primary skills, she will use them to
play the game and will very likely either deduce combinations that work as second-
ary skills or stumble on those combinations by accident. However, if she missed a
primary skill (for example, she never pressed the button to shoot), she might never
realize that shooting was an option and miss out on an entire branch of the skill tree.
The skill atoms work very well with dexterity-based action games in which each skill
atom maps to mastering the controls to play the game. However, it can be applied
just as easily to more strategic games whose challenges don't depend on mastery of
the controls. For example, in a turn-based strategy game, skill atoms might include
the player understanding that a cavalry unit is very effective at fighting units of
archers. The steps to learn this skill are similar to any action-based skill atom. The
player needs to perform an action (order cavalry to attack archers), and the game
runs a simulation (decides how effective the attack is) and provides feedback (ani-
mations and visual effects to indicate the effectiveness of the attack) that allows the
player to update her mental model (attacking archers with cavalry is effective).
