reasoning is the AI capability to take into account terrain in its planning,
decisions, actions and communication. Terrain reasoning is a necessity
if both AI and terrain play an important role in the game -- as is often
is the case in 3D action games.
Level designers spend weeks designing a challenging game world with well-thought
out battle arenas, multiple access routes, risky approaches to highly
valued power-ups, defensive strongholds, and neutral zones.
However, the traditional action game AI was unaware of all the thoughts,
efforts and design that went into the level. Instead, it ran around almost
blind, via shortest paths and sometimes guided by a few static hints from
the level designer:"Don't ask me, I only work here!"
This article presents terrain reasoning based on the waypoint graph typically
present in 3D action games. It discusses terrain reasoning concepts, and
how the waypoint graph can be reasoned about. The paper discusses and
demonstrates the relation between tactics and terrain. A case-study shows
how to develop off-line and in-game reasoning to pick good sniping spots,
and how to use game-play feedback to create adaptive AI with tactical
understanding of the terrain.
A short threat prediction example demonstrates one of other ways to reason
about the terrain. The paper also addresses the major issues in implementing
such a terrain reasoning system.
Today's action games offer plenty of situations where better AI understanding
of the terrain would be valuable to the gamer and level designer. For
key terrain features and communicating about them.The player issues
a "provide suppressive fire" command while pointing to a door
in a distant building. Typically, it is not as obvious to the AI as
it is to the player that a door is pointed to rather than the wall next
to it. But the player expects to hear the AI confirm his order: "roger,
will provide fire on that door".
between good and bad locations. All locations are not created equal.
Some locations are great to ambush other actors, whereas other locations
are not. An AI actor who picks the right location for an action simply
is more convincing
location based performance. After being lured into the same narrow tunnel
to receive a rocket for the 3rd time in a row, it would be great if
the AI would recognize the tunnel as a bad place to be. The AI should
adapt its tactics accordingly, instead of trying to dodge the rocket
without the space to do so.
part of the level annotation. The level designer favorite job probably
isn't manually editing dozens of waypoints to tell the AI "camp
here", "avoid this location", "here's some cover".
An AI capable of automatically annotating the level itself will save
the level designer time. And AI provided feedback on its interpretation
of the terrain might be welcome as well. Automated AI interpretation
not only is useful for the professional level designer, but even more
for the amateur level designer who is less familiar with the needs of
the terrain in tactical considerations. Few things are as exciting as
engaging a squad of AI actors who coordinate their actions, and alternate
suppression fire with grenade lobbing. Part of that excitement disappears
if the same squad applies those same tactics at a less suitable location:
the AI should understand that attacking from, for example, an elevator
is different than from a warehouse full of crates.
may be an important ingredient to address the issues, but it cannot do so
without enhancements in other parts of the AI, such as the planner, state
machines, combat rules, etc. These other parts of the AI have been receiving
plenty of attention in literature.
Terrain reasoning AI subsystem consists of the following components:
- terrain representation; and
- functions to construct, query and manipulate that terrain representation.
of terrain in an action game makes it infeasible to efficiently handle
the terrain in raw geometry format, or by means of a rule bases or neural
nets: both the size and the geometric detail present in a level prevent
For those reasons, terrain reasoning should be addressed with custom solutions,
tuned for the specific AI needs and level characteristics of the game.
A popular and custom means to describe terrain are waypoints (and similar
concepts such as cells or grids - see [Reece], [Snook]). Waypoints represent
the subset of the terrain accessible to the player and AI. The connections
between these waypoints denote viable movement. And the graph created
by the waypoints and their inter-connections expresses the valid paths.
Often, these waypoints are annotated with the presence of nearby power
ups. Sometimes, the waypoints are part of more abstract concepts like
areas and portals. Thus, waypoints are a handy and versatile terrain representation.
Nevertheless, the AI typically ignores to reason about them (except for
the occasional path finding).
The remainder of this paper discusses how to reason about terrain based
on the waypoint graph. While the ideas result from developing tactical
squad and individual AI for tactical action game, the concepts apply to
a wide range of action games.