As the video game industry continues to grow and expand, many developers and publishers are on a quest to find more cost- and time-efficient methods of developing their products, especially as budgets continue to grow for high-profile titles. A new study from researchers based out of North Carolina State University claims that they are able to accurately predict the behavior patterns of gamers, allowing developers to view what their players are interested in and create content specifically for those needs.

Dr. David L. Roberts, an assistant professor of computer science at NCSU and coauthor of the research paper, was generous enough to answer a few of our questions regarding his studies, his findings, and how developers could potentially implement these ideas into the development process. Dr. Roberts is no stranger to video games, growing up with classics such as King's Quest and Conquests of Camelot, but now he spends the majority of his time studying them instead.

"I got interested in this while a graduate student working on interactive narratives," Roberts told Ars. "I feel like developers put a lot of thought into the content they push out to players; however, that content can be somewhat restrictive as it is 'one size fits all' or, in some more extreme cases, is forced upon players. We are hoping to get to a point where game content is highly dynamic, customizable, and adapted based on individual players."

Roberts and his coauthor, Brent Harrison, set out to analyze the behavioral patterns of gamers and subsequently create a method in which observers could predict the actions of those playing games. The team decided that a persistent, open-world online game would be the prime setting for their research and began their work in the massively popular MMORPG World of Warcraft.

Data pulled directly from the servers

The researchers combed through data for 14,000 players, examining playtime and earned achievements provided by the WoW Armory, a popular Web database used for tracking data and progress for every player in World of Warcraft. According to Roberts' research paper, they were only concerned with a character's achievement information. In WoW, achievement badges are representations of game content that players have experienced. Some achievements are standalone, while others are part of a sequence or batch of rewards, which Roberts refers to as "cliques of actions."

In most games, achievements are milestones for completing certain stages or progressing through specific portions of a game. World of Warcraft's achievement system rewards players for completing quests, reaching milestone experience levels, obtaining mounts, exploring the world map, raiding dungeons, and so on. Some are simple and easy to acquire, while most others require a level of dedication to receive. Roberts and Harrison were able to assume that if a player had completed a specific achievement, it served as a measurement of the same player's interest in that particular action.

Data in hand, the team began work on an algorithm to pinpoint correlations between random players and the achievements they have unlocked.

"There are two phases to our approach," Roberts explained. "In the first phase, we look at the data generated by a large number of players to identify common co-occurrences of specific achievements. For example, if 5,000 players have all completed the same five achievements, we say those five achievements are highly correlated. We build our model by finding as many of these common co-occurrences as we can. In the second phase, where predictions are made, a new player is compared against the set of common co-occurrences. If they have completed three of the five achievements that commonly co-occur, we can predict they will complete the remaining two."

Roberts was able to predict a player's next action based on their previous behavior with 80 percent accuracy. With this research, he believes that game developers can implement a system in which gamers can be funneled towards destinations or encounters through the use of achievement rewards. However, Roberts also adds that other genres beyond MMORPGs could also benefit from his findings.

"The genres of games that will benefit most from this technique are likely to be sandbox environments, like MMORPGs," he said. "An FPS is often linear in its gameplay, and therefore it is unlikely to produce any data that is interesting for making predictions; however, sandbox-style FPS games could absolutely work. For example, logging the locations, targets, and weapons used for each kill in PvP mode would enable us to predict future locations, targets, and weapons, et cetera."

"Achievements in WoW are a natural fit, but aren't the only data we can handle," Roberts continued. "Our technique is applicable to any game that produces sequential observations of players' behaviors or decisions. In a game like the classic Tetris, however, the progression of the game does not lend itself naturally to being modeled by sequential observations of player decisions."

While fascinating, the research done so far is only calculated from data tables of player information. The next logical step is live tests, but according to their research, there are a number of major obstacles preventing that. They would have to create and distribute their own software that players would use in-game while also completing surveys to determine how well the program is evaluating their decision-making. Roberts notes that surveys are often never completed, leaving a potentially low response rate for this type of experiment. Regardless, the team hopes to find new applications of their research in the near future.

Roberts' paper, "Using Sequential Observations to Model and Predict Player Behavior," will be presented at the Foundations of Digital Games Conference in Bordeaux, France, which runs from June 29 to July 1.