Antonio J. Fernández Leiva

Game programming and serious games

Procedural Content generation: the 3 main goals..

PCG: The case of Oil Rush

PCG: The case of Oil Rush


The videogame industry has taken the lead role from the entertainment business, with a total consumer spent of $24.75 billion in 2011 [1] and estimated game revenues of $70.4 billion worldwide in 2013 (which represents a 6% year-on-year increase), according to Newzoo’s 2013 Global Games Market Report [2]. Moreover, the number of gamers was expected to surpass 1.2 billion by the end of that year. This situation has motivated the research applied to videogames, which has been acquiring notoriety during the last years, involving many areas such as psychology and player satisfaction, marketing and gamication, computational intelligence, computer graphics, and even education and health (serious games). The quality and appealing of video-games used to rely on their graphical quality until the last decade, but now, their attractiveness falls on additional features such as the music, the player immersion into the game and interesting storylines. It is hard to evaluate how amusing a game is because this evaluation depends on each player, nevertheless there is a relationship between player satisfaction and fun [3]. Nowadays, interesting new challenges and goals are emerging within the area of video games, especially in the field of articial and computational intelligence in games [4].

As I have already mentioned in a previous post, Procedural Content Generation (PCG) [5, 6] refers to the algorithmic creation of game content, either with human intervention or without it, such as maps, levels, textures, characters, rules and quests, but excluding the behavior of non-playable characters (what is considered in the scientific community as generation of game AI and not content generated procedurally….difference that might be the issue to discuss in  a  future post 😉  and the game engine itself.  The use of PCG has several advantages, including saving memory and disk space, improving human creativity and providing adaptivity to games. These benets are well known by the industry as demonstrated by the use of PCG techniques during the development of commercial games such as Borderlands saga with procedurally generated weapons and items, Skyrim (terrains and forests), and Minecraft or Terraria with procedurally generated worlds. We are thus in front of an exciting field that can controbute siginificantly to change the mechanism of producing(implementing videogames.

At the moment, there are three main goals [5] of PCG research that are currently not obtainable and it would require signicant further research effort:

  • Multi-level multi-content PCG (i.e. systems that are able to generate multiple types of quality content at multiple levels of granularity in a coherent fashion while taking game design constraints into consideration),
  • PCG-based game design (i.e. creating games where a PCG algorithm is an essential part of the game instead of being a design tool) and
  • PCG systems that could create complete games including the rules and game engine.

Are you ready to take up the challenges?




Three exciting goals with no doubt! But also three really-very-difficut-to-handle challenges! Precisely, to deal with PCG and its main goals the SME SERIGAMES Spain S.L.  have been recentñy created (well, to be honest, we are taking decisive steps in its creation)….I hope I can tell you more about this company in a near future……..



[1] Entertainment Software Association, Essential facts about the computer and video game industry (2012). URL
[2] T. Hagoort, P. Warman, 2013 global games market report, Tech. rep., Newzoo, accessed 20 Jan 2014 (2013). URL
[3] M. Nogueira, C. Cotta, A. J. Fernandez-Leiva, On modeling, evaluating and increasing players’ satisfaction quantitatively: Steps towards a taxonomy, in: C. D. Chio, et al. (Eds.), Applications of Evolutionary Computation, Vol. 7248 of Lecture Notes in Computer Science, Springer-Verlag, Malaga, Spain, 2012, pp. 245{254.

[4] S. M. Lucas, M.Mateas, M. Preuss, P. Spronck, J. Togelius (Eds.), Articial and Computational Intelligence in Games, Vol. 6 of Dagstuhl Follow-Ups, Schloss Dagstuhl – Leibniz-Zentrum fuer Informatik, 2013.

[5] J. Togelius, A. J. Champandard, P. L. Lanzi, M. Mateas, A. Paiva, M. Preuss, K. O. Stanley, Procedural Content Generation: Goals, Challenges and Actionable Steps, in: S. M. Lucas, M. Mateas, M. Preuss, P. Spronck, J. Togelius (Eds.), Articial and Computational Intelligence in Games, Vol. 6 of Dagstuhl Follow-Ups, Schloss Dagstuhl{Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, 2013, pp. 61{75.

[6] M. Hendrikx, S. Meijer, J. Van Der Velden, A. Iosup, Procedural content generation for games: A survey, ACM Trans. Multimedia Comput. Commun. Appl. 9 (1) (2013) 1:1-1:22.

 Note: Part of this post has been taken (and adjusted) from a paper of mine co-authorised with Carlos Cotta and Raúl Lara-Cabrera that have been submitted for publication in a reserach journal.

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