this is the third installment of our ongoing survey of AI middleware
tools targeted at game developers, we examine RenderWare AI 1.0,
a suite of C++ base classes. RenderWare AI (RWAI) was developed
by Kynogon, a French company specializing in game AI (it developed
the Kynogon Artificial Intelligence Modules, or KAIM), and is packaged
as a part of RenderWare Platform, Criterion's suite of game development
products. Discussion of the entire suite of RenderWare products,
which also includes graphics, audio and physics tools, is beyond
the scope of this article, which only focuses on RWAI. That being
said, it would give RWAI short-shrift if we ignored the support
the various other RenderWare Platform components provide RWAI (graphics
representation of world data and the physics collision detection
and visibility services, to name a few). Therefore, where appropriate,
the services of the non-RWAI components of the RenderWare Platform
will be pointed out when they can be used by the RWAI.
this AI Middleware product do for the game developer?
RWAI Software Development Kit (SDK) primarily focuses on helping
the game developer design and implement character behavior in a
computer game. In doing so, the RWAI SDK provides services for modeling
the world, the objects that occupy the world and then the characters
that exercise behavior within the world. RWAI views the objects
in the world as entities, in two basic forms: thinking entities
and passive entities.
entities are typically NPCs, or what some games refer to as "agents".
Thinking entities have a brain object that enables decision-making
capabilities, which in turn can select behaviors to be carried out.
Passive entities are typically objects that exist in the virtual
world and interact with thinking entities, but are not under the
control of the RWAI. More about entities will be presented in a
moment, but first let's look at an overview of the services that
RWAI SDK provides these services in a multi-layered environment:
Decisions layer supports the brain objects just mentioned.
When a thinking entity is created, a brain object for that entity
is also created and initialized. The brain object performs the decision-making
process. Based on how the brain is initialized, and the current
status of the entity, the brain object will select an agent (or
behavior) to be carried out by the entity.
Agents layer supports behavior packages that can be carried
out by entities. So the term "agent", as used in RWAI,
actually refers to a set of actions that reflect a high-level behavior.
Some RWAI agents are: Go To, Follower, Follow Path, Wanderer, Runaway,
Hider, Contact Combat and Distant Combat. Additional agents can
be defined by the game developer and added to the brain objects.
Services layer consists of a number of manager objects that
provide specific services to RWAI and by proxy to the entities.
There is a NextMove Manager which is used to find paths for characters
in the world, a Graph Manager which manages path data that reflects
the virtual world in which paths can be found, a PathWay Manager
that stores pre-calculated paths for use by entities, a PathObjects
Manager that supports access to all the non-entity objects that
can participate in a path finding effort (doors, elevators, ladders),
an Entity Manager which provides visibility and proximity services
for entities, a SoundSources Manager which represents the audio
and olfactory perception facilities for entities, and finally a
NeuralNet Manager which manages all the data for neural nets used
Architecture layer handles the initialization, updating and
termination of the RWAI layers under the control of the game engine.
The performance configuration of RWAI can be maintained using this
layer, tuned to correspond to the needs of the game and platform
in use. This layer is also responsible for exchanging information
between the game engine and the other RWAI layers.
the main features of this AI Middleware product?
offers a number of AI-related services and features that are worthy
of a little more detailed examination. First, the 3D pathfinding
service of RWAI is supported by the cooperative functionality of
several objects found in the Services Layer. The CNextMoveManager
object provides the basic service of finding a path along a graph
using the A* Algorithm (the A* is one of the most widely used search
algorithms for computer game pathfinding functions). With the availability
of the CNextMoveManager
object source code, you can modify this process, as needed, to suit
specific game needs. The graph used for pathfinding is supported
by the CGraphManager
object that manages all the PathData
objects specific to a given level (or section) of the virtual world
of the game. A PathData
editor and Automatic Path Generation process are available for creating
and maintaining the PathData
management can be performed in RWAI using the Entity API. Both thinking
and passive entities must be created and placed in the world known
to RWAI in order to affect how decisions are made and the services
that can be provided. Basically, entities are created, added to
the world, updated, queried for basic information (size, location,
speed) and destroyed via the RWAI Entity API. The type of brain
a thinking entity uses can be determined using entity management,
and once the type of brain has been determined, the available default
agents that the entity can use are also determined. Of course, passive
entities do not use brains, they just exist and interact with thinking
RWAI provides dynamic avoidance by entities by using predefined
agents (once again, "behaviors" as Criterion defines the
term) such as Hider and Runaway. An entity brain can select the
Hider Agent and that entity will attempt to move to a hiding place
that is out of sight of the entities that are defined as being its
enemies. If the Runaway Agent is selected for execution, then the
entity will flee from entities that are defined as being its enemies.
entity manager supports the 3D perception services for entity brains
and agents. These services include determining the visibility of
an entity, determining the distance between entities and identifying
the nearest enemy entity. An optional service is a Sound Manager
that provides sound event perception for entities.
RWAI, agents represent pre-packaged behaviors that can be associated
with a brain object and thus provide entities with the ability to
perform these behaviors without additional user control. At the
time of this writing, these agents consist of:
- directs an NPC to a specific destination.
- enables an NPC to follow a specific entity, from a defined distance
and at a defined bearing.
- directs an NPC to move away from a set of locations and to stop
when hidden from all of them.
- directs an NPC to follow a series of way points, that form a
- enables an NPC to wander to random destinations.
- directs an NPC to hide out of sight, of specific entities.
- enables an NPC to move into a firing position and shoot at a
targeted enemy with the current weapon, based on line-of-sight
and weapon ranges.
- enables an NPC to fight a targeted enemy in melee combat, using
- provides a testing and debugging agent tool to the game developer
for use prior to any agent modification or development.
observant reader will notice that the RWAI agents are declared as
C++ objects, and as such, are provided with public access functions
to allow you to set parameters that control the behavior executed
within each agent. Also, as C++ objects, if you are interested in
extending your own behaviors you can derive them from the base agent
objects, inheriting their basic functionality to which your own
may be added.
RWAI relies on XML file-based configurations for setting up default
parameters and associating various components to the overall system.
Here is an example of the XML used for configuring the main level
of the game:
example in Figure 2 shows the level is given a Name ("termitiere"),
the value of OneMeter is provided in game units, the MaxEntity value
indicates the maximum number of entities supported on this level,
Tpf specifies the CPU time per frame that the core KAIM uses, and
the name of the RawDataFile for the level. Additional sections of
the XML file provide for declarations of Global Services, as shown
in Figure 3.
Slicing information in the TimeMgt section is shown in Figure 4.
types of XML definitions continue for various sections: entities,
brains, agents and services.
mentioned above, most of the RWAI services are fully open modifiable
source code, which means that extensibility and modification of
RWAI by game developers is highly possible.
the game developer implement this AI Middleware product in a game?
mentioned at the beginning of the article, RWAI is part of a larger
suite of game development tools by Criterion, called the RenderWare
Platform. If the graphics and physics components of the RenderWare
Platform are also in use, then RWAI will access services provided
by those components to give it knowledge about the world, line-of-sight
and collision detection, and other services. In the absence of those
components, RWAI will rely on your game engine for those services.
the implementation approach discussed in this article assumes the
developer's game engine provides services to the RWAI. Access to
RWAI through the API comes via three forms: access to the engine,
to the world and to entities.
the RWAI Engine API lets you open and initialize the RWAI to set
performance parameters, establish certain callbacks (to provide
services such as collision and visibility detection), and set callback
functions for path data services. By using the RWAI World API, the
game developer can load, update and free AI World data to be used
by the RWAI services for the game. If the RenderWare Platform Graphics
component is in use, then the AI World gets its data from the world
supported by the Graphics. Another function of the RWAI World API
is to manage families (groups) of entities and to support the existence
of the entities themselves. While entities are added to the AI World
by using the RWAI AI World API, the entities are actually created
by using the RWAI AI Entity API. When an entity is created, it is
associated with an existing entity family (a group of similar entities)
and then added to the AI World. Once the entity is no longer needed,
the RWAI AI Entity API supports the removal of the entity from the
AI World and the entity's destruction.
set of callback functions must be associated with the entity, to
tell RWAI how the entity is updated from game engine data, how RWAI
control actions can be translated into a command that the game engine
can understand how to execute, and how user defined decisions are
made. RWAI Entities can rely on RWAI Agents for default and standard
behavior. As noted earlier, there are a number of agents available
for selection in order to implement this pre-defined behavior. If
custom behaviors by entities are required, the set of behaviors
available to entities can be extended. Extending a behavior is accomplished
by deriving the developer's own classes from the KAIM base classes
that form the core of the RWAI behaviors. This however, can constrain
the developer by having to conform to the KAIM protocols and decision-making
processes, rather than plugging his own decision-making processes
directly into the KAIM.
RenderWare AI Middleware
is a powerful AI middleware SDK, and when used in conjunction with
the other RenderWare Platform components, it is a robust solution.
Even when you use RWAI by itself and have your game engine provide
the services of the RenderWare Platform, the SDK is capable of implementing
sophisticated character behavior. Such performance comes at a price
however, in terms of the learning curve to be able to integrate
RWAI into the game engine, and the constraints imposed by the KAIM
based on how it must operate.