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Comment: Re:Yavalath (Score 1) 112

by jtogel (#43629293) Attached to: AI System Invents New Card Games (For Humans)
Yes, Cameron's work was one of our sources of inspiration. The Ludi system that produced Yavalath is clearly a milestone in research on automatic game design. Another source of inspiration was my own work on automatic game design for simple PacMan-like games, which was carried out at the same time as Cameron's work and is described in this paper:
http://julian.togelius.com/Togelius2008An.pdf
In general, this line of research is still in its infancy, as we are trying to figure out new ways of evaluating game quality and representing various aspects of games.

Comment: Some additional info (Score 1) 112

by jtogel (#43627859) Attached to: AI System Invents New Card Games (For Humans)
The original papers describing the work can be found here:
http://julian.togelius.com/Font2013Towards.pdf
and
http://julian.togelius.com/Font2013A.pdf

Similar evolutionary techniques have been used to generate a number of different types of game content, including Starcraft maps, Super Mario levels, rocks, dungeons, weapons... Here's an overview:
http://julian.togelius.com/Togelius2011Searchbased.pdf

+ - AI system invents new card games (for humans)->

Submitted by jtogel
jtogel (840879) writes "This New Scientist article describes our AI system that automatically generates card games. The article contains a description of a playable card game generated by our system. But card games are just the beginning... The card game generator is a part of a larger project to automatise all of game development using artificial intelligence methods — we're also working on level generation for a variety of different games, and on rule generation for simple arcade-like games."
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AI

+ - How does modularity evolve?-> 1

Submitted by
JimmyQS
JimmyQS writes "As programmers know, modularity is critical to making reusable, adaptable software. However, modularity is not instinctive for beginners and must be learned via painful training. Biology faces a similar problem: modularity is useful to make species more adaptable, but how did it evolve in the first place? Surprisingly, computational simulations of 25,000 generations of evolution reveal that modularity does not evolve because it makes organisms more adaptable. Instead, modularity evolves as a by-product for selection to reduce the "wiring costs" of a network. The discovery greatly advances research into evolving artificially intelligent robots, a field where the inability to evolve modular designs has long been thought to be a key roadblock to evolving truly complex, intelligent neural networks.

The paper was published in the Proceedings of the Royal Society. You can also watch modularity evolve in this video."

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AI

+ - Create your own Monopoly to understand the world around you->

Submitted by
jtogel
jtogel writes "Can we use games to help people explore the massive amounts of data that are increasingly available to everyone? In a recent paper, which New Scientist write about here we describe a program that can generate Monopoly Boards from open data streams. The player selects what is important to him or her (child poverty? education? median income?) and the program uses AI methods to create a new game board. The full paper is available here."
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Crime

+ - Girl uploads photo of money to Facebook, Family robbed->

Submitted by mask.of.sanity
mask.of.sanity (1228908) writes "Robbers armed with a knife and a wooden bat attacked an Australian family after their 17 year-old daughter uploaded a photo of cash to Facebook.

The daughter lived in Sydney some 150 kilometres away where she took the photo while helping to count her grandmother's life savings.

It was unknown how much money was counted or how the thieves obtained her family's home address."

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Comment: Important clarification (Score 1) 114

by jtogel (#31981690) Attached to: IEEE Introduces Mario Level-Generation Competition
The aim of the competition is not merely to create random levels, but to generate levels that are tailored to particular players' playing styles and skills. The level generator gets as inputs how well a player performed on a test level and various metrics detailing e.g. how much time the player spent jumping and running and how many fireballs were fired. The level will then be judged by the player who played the test level. See more about the rules at: http://www.marioai.org/LevelGeneration/Interface Also, please note that those who submit a level generator can also submit a paper about it to the CIG conference. http://game.itu.dk/cig2010/?page_id=483

+ - New AI challenge is all about wanton destruction->

Submitted by
togelius
togelius writes "Previous years have seen a number of car racing competitions where neural nets, rule-based systems and other fancy AI techniques have been put to the test by letting them drive on a track and seeing who gets the best lap time. Recognizing that finding the Michael Schumacher of AI is not enough, a team of researchers from University of Wuerzburg now wants to find the Mad Max of AI. Their new competition is called "Demolition Derby" and the goal is to "wreck all opponent cars by crashing into them without getting wrecked yourself". For this, they use the open-source TORCS game and a custom AI interface, allowing all and any AI researchers and enthusiasts (including you!) to submit their best and most aggressive controllers."
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Games

+ - Should computer games adapt to the way you play?-> 1

Submitted by
jtogel
jtogel writes "Many games use "rubberbanding" to adapt to your skill level, making the game harder if you're a better player and vice versa. Just think of Mario Kart and the blatantly obvious ways it punishes you if you drive too well by giving the people who are hopelessly behind super-weapons to smack you with. It's also very common to just increase the skill of the NPCs as you get better — see e.g. Oblivion. In my research group, we are working on slightly more sophisticated ways to adapt the game to you, including generating new level elements based on your playing style.

Now, the question is: is this a good thing at all? Some people would claim that adapting the game to you just rewards mediocrity (you don't get rewarded for playing well). Others would say that it restricts the freedom of expression of the game designer. But still, game players have very different skill levels and skill sets when they come to a game, and we would like to cater to them all. And if you don't see playing skill as one-dimensional, maybe it's possible to do meaningful adaptation? What sort of game adaptation would you like to see? I'm very interested in your feedback here..."

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Comment: Re:Play style is not a constant (Score 1) 167

by jtogel (#29038945) Attached to: Classifying Players For Unique Game Experiences
Well, there is nothing in the article (or in our research program as a whole) that says that playing styles are static. What's (more or less) static are models of player style/player preferences. Once we have the model, we can re-categorize you every time you play. This way we can do adaptive difficulty, amongst many other things.
XBox (Games)

+ - In the Underworld, the game plays you!->

Submitted by
togelius
togelius writes "Whenever you play a game of Tomb Raider: Underworld, heaps of data about your playing style is collected at Eidos' servers. Researchers at the Center for Computer Games Research have now mined this data to find out who you are! Using self-organizing neural networks, they classified players as either Veterans, Solvers, Pacifists or Runners. It turns out people play the game for very different reasons and focus on different parts of the game, but almost everyone falls into one of these categories. These neural networks can now instantly find out which of these you belong to based on just seeing you play. In the near future, such networks will be used to adapt games like Tomb Raider while they are played (e.g. by removing or adding puzzles and enemies), so you get the game you want."
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