![](bga.png)
ated by modularization due to the extra activations is
less than the benefit gained from it.
6 CONCLUSIONS AND FUTURE
WORK
To improve the usability of multi-domain content gen-
eration, the selected content domains for generation
as well as the order and manner in which it is gener-
ated should be configurable. We presented an exten-
sible framework for multi-domain content generation
of virtual worlds. We have introduced blackboards
to the domain of procedural generation to alleviate
the current limitations of multi-domain content gen-
eration. Encapsulating the different (single content-
domain) procedural methods into knowledge sources,
allows the system to reason about the generation pro-
cess which in turn allows optimization of the gener-
ation process by eliminating unnecessary generation
executions and ordering the remaining based on pri-
ority in terms of content dependencies.
We provided an overview of the design consider-
ations when using our method for virtual world gen-
eration: modularization and knowledge source design
patterns. We have shown the extensibility of our sys-
tem by implementing a set of 3 different use cases
(forest, road and combined environments) which form
a representative sample set of virtual world genera-
tion. Furthermore, our system facilitates a more sta-
ble way of editing generated content, as changes in
the data only trigger the specific procedural meth-
ods that depend on it. Finally, the generation perfor-
mance of the system depends on the scheduling sys-
tem (i.e. event reduction) and modularization design
paradigms. Event reduction reduced the number of
knowledge source activations by as much as 98% re-
sulting in better performing large world generation.
Although modularization increases the number of ac-
tivations, we proved that the overall runtime can be re-
duced by intelligent data and knowledge source reuse.
For paths for future research, we suggest five pos-
sible extensions. Firstly exploring the behaviour of
dependency cycles in the data model. Secondly, im-
proving the editing of generated content by automat-
ically communicating edits to the knowledge source
that created said changed content. Thirdly improving
the generation performance of the system by for ex-
ample automatic concurrency of the PCG blackboard
architecture. The separation of procedural modelling
methods into knowledge sources should provide op-
portunities for parallelization. Fourthly, data ontolo-
gies could be utilized to provide a formalized data for-
mat, allowing for more optimizations for scheduling
and overall improvement of the coherence of the re-
sulting content. Lastly recursive blackboards could
be used for PCG blackboards, where the knowledge
sources can contain blackboards themselves. This
could be used to enable scoping operations, where
certain knowledge sources are scoped within certain
regions of the virtual worlds. This would allow finer-
grained control over the generation process and allow
different types of constraints in different regions.
REFERENCES
Corkill, D. D. (1991). Blackboard systems. AI expert,
6(9):40–47.
Dormans, J. (2010). Adventures in level design: generat-
ing missions and spaces for action adventure games.
In Proceedings of the 2010 workshop on procedural
content generation in games, page 1. ACM.
Esri (2016). Esri cityengine 3d modeling software for
urban environments. http://www.esri.com/software/
cityengine/. Consulted August 2016.
Ganster, B. and Klein, R. (2007). An integrated frame-
work for procedural modeling. In Proceedings of the
23rd Spring Conference on Computer Graphics, pages
123–130. ACM.
Genevaux, J.-D., Galin, E., Peytavie, A., Guerin, E., Bri-
quet, C., Grosbellet, F., and Benes, B. (2015). Terrain
modelling from feature primitives. Computer Graph-
ics Forum, 34(6):198–210.
Grosbellet, F., Peytavie, A., Gu
´
erin, E., Galin, E., M
´
erillou,
S., and Benes, B. (2015). Environmental Objects for
Authoring Procedural Scenes. Computer Graphics
Forum, 35(1):296–308.
Gurin, E., Digne, J., Galin, E., and Peytavie, A. (2016a).
Sparse representation of terrains for procedural mod-
eling. Computer Graphics Forum (Proceedings of Eu-
rographics 2016), 35(2).
Gurin, E., Galin, E., Grosbellet, F., Peytavie, A., and
Gnevaux, J.-D. (2016b). Efficient modeling of entan-
gled details for natural scenes. Computer Graphics
Forum, 35(7):257–267.
Hartsook, K., Zook, A., Das, S., and Riedl, M. O. (2011).
Toward supporting stories with procedurally gener-
ated game worlds. In 2011 IEEE Conference on Com-
putational Intelligence and Games (CIG’11), pages
297–304. IEEE.
Kelly, G. and McCabe, H. (2007). Citygen: An interac-
tive system for procedural city generation. In Fifth
International Conference on Game Design and Tech-
nology, pages 8–16.
Mateas, M. and Stern, A. (2002). A behavior language for
story-based believable agents. IEEE Intelligent Sys-
tems, 17(4):39–47.
Misztal-Radecka, J. and Indurkhya, B. (2016). A black-
board system for generating poetry. Computer Sci-
ence, 17(2):265.
Extensible Multi-domain Generation of Virtual Worlds using Blackboards
91