7. Pier Luca Lanzi – 20 Luglio 2018 – Campus Party
Balancing Multiplayer First-Person Shooters
• Providing the “right amount” of challenge is very important. Multiplayer
games are more difficult to balance
• Balance depends on the players’ skill, the playing strategies, the
game environment, the weapons, etc.
• How can we evaluate if an FPS is balanced? It is mainly subjective!
However, the distribution of kills/scores among players could be a
good proxy
• For example, in a 2-players match best player should kill the opponent
less than twice the time it has been killed
7
21. Pier Luca Lanzi – 20 Luglio 2018 – Campus Party
AI Framework to Assist Level Designers
• Conceptual model
Graph representation of levels
Probabilistic estimation of difficulty
• Definition of a set of metrics to evaluate
levels in terms of difficulty and probability of completion
• Model validation
Single jumps human playtesting
Double jumps human playtesting
• Implementation in Unity editor
21
22. Pier Luca Lanzi – 20 Luglio 2018 – Campus Party
Components of the conceptual model
• Jumps
Trivial, Simple, Falling, Reentrant
• Platforms
Static
Moving
Fading
Spiked
• Game elements
Enemies
Collectible items
22
34. True or Generated?
Random Vector
DOOM Levels
Generated Levels
D Network
G Network
Area Convex?
Main Axis # Rooms
… …
35.
36. Pier Luca Lanzi – 20 Luglio 2018 – Campus Party
Data-Driven Game Design
• Video games can generate and collect huge amount of
data
• These data contain potentially useful information that can
help improving the design or inspiring new designs
• Advanced data mining methods are required to analyze
such data so as to produce models and knowledge to
support designers
36
37. Pier Luca Lanzi – 20 Luglio 2018 – Campus Party
References
• Luigi Cardamone, Pier Luca Lanzi, Daniele Loiacono:TrackGen: An interactive track generator for TORCS
and Speed-Dreams. Appl. Soft Comput. 28: 550-558 (2015)Player Modeling
• Luigi Cardamone, Pier Luca Lanzi, Daniele Loiacono, Enrique Onieva:Advanced overtaking behaviors for
blocking opponents in racing games using a fuzzy architecture. Expert Syst. Appl. 40(16): 6447-6458
(2013)
• Daniele Loiacono, Luigi Cardamone, Pier Luca Lanzi:Automatic Track Generation for High-End Racing
Games Using Evolutionary Computation. IEEE Trans. Comput. Intellig. and AI in Games 3(3): 245-259
(2011)
• Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi:Learning to Drive in the Open Racing Car Simulator
Using Online Neuroevolution. IEEE Trans. Comput. Intellig. and AI in Games 2(3): 176-190 (2010)
• Daniele Gravina, Daniele Loiacono:Procedural weapons generation for unreal tournament III. GEM 2015: 1-
8
• Luca Galli, Pier Luca Lanzi, Daniele Loiacono:Applying data mining to extract design patterns from Unreal
Tournament levels. CIG 2014: 1-8
• Pier Luca Lanzi, Daniele Loiacono, Riccardo Stucchi:Evolving maps for match balancing in first person
shooters. CIG 2014: 1-8
• Pier Luca Lanzi, Daniele Loiacono, Emanuele Parini, Federico Sannicoló, Davide Jones, Claudio
Scamporlino:Tuning mobile game design using data mining. IGIC 2013: 122-129
• Daniele Loiacono:Learning, evolution and adaptation in racing games. Conf. Computing Frontiers 2012:
277-284
• Matteo Botta, Vincenzo Gautieri, Daniele Loiacono, Pier Luca Lanzi:Evolving the optimal racing line in a
high-end racing game. CIG 2012: 108-115
37