New software to better predict player goal in video games

Scientists have developed an artificial intelligence (AI) software for video games that is significantly better than any previous technology at predicting what goal a player is trying to achieve.

The advance holds promise for helping game developers design new ways of improving the gameplay experience for players.

"We developed this software for use in educational gaming, but it has applications for all video game developers," said Dr James Lester, a professor of computer science at North Carolina State University.

"This is a key step in developing player-adaptive games that can respond to player actions to improve the gaming experience, either for entertainment or - in our case - for education," said Lester.

The researchers used "deep learning" to develop the AI software. Deep learning describes a family of machine learning techniques that can extrapolate patterns from large collections of data and make predictions.

In this case, the large collection of data is the sum total of actions that players have made in a game.

The predictive AI software can then draw on all of that data to determine what an individual player is trying to accomplish, based on his or her actions at any given point in the game.

And the software is capable of improving its accuracy over time, because the more data the AI program has, the more accurate it becomes.

To test the AI programme, researchers turned to an educational game called "Crystal Island," which they developed years earlier.

While testing Crystal Island, the researchers amassed logs of player behaviour (tracking every action a player took in the game) for 137 different players.

The researchers could tell the AI everything a player had done in Crystal Island up to a certain point and see what goal the AI thought the player was trying to accomplish.

By checking the AI's response against the player log, the researchers could tell whether the AI was correct.

"For games, the current state-of-the-art AI programme for goal recognition has an accuracy rate of 48.4 per cent," said Wookhee Min, a PhD student at NC State and lead author of the research paper.

"The accuracy rate for our new programme is 62.3 per cent. That's a big jump," said Min.

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