Adaptive Difficulty

By: Lewis Sykalski

The Problem The Proposal

Video games get boring quickly. Especially if they are too easy. That's why there is the miracle of difficulty. They breathe new life into video games by allowing the user to specify a level (eg. easy, medium, hard) that he will find challenging but at the same time not too difficult. Remember, he must still be able to progress in the game. This difficulty discover.

and error.

setting is often hard to Most often it comes from trial The player must keep retrying via trial and error to find his "optimum" difficulty setting, but this is sometimes a long and tedious process.

Wouldn't it be cool if the computer could do the work for you? Breathing new life into games is possible, without all that tedious work that goes along with it. I propose using a neural network to solve the difficulty problem. By keeping track of any player's history, the neural network can assess the player’s skills and find the player’s "optimum" difficulty setting. I intend to demonstrate this on a game very near and dear to all gaming enthusiasts—Space Invaders.

The Network

I will use a MLP network to solve the difficulty problem.

abandoned the idea.

The input feature space is shown below as well as the sole output difficulty. I planned to try to do a one-hot implementation but I have since • • • • •

Feature Space

High Score-the highest score this player has reached Total Score-the total score of all games played by this player Avg. Score-the avg. score over all games played by this player Games- The total number of games this player has played Level- The level reached on the last game played by this player •

Output

Difficulty-The difficulty setting for this round of play

Meet The Players

Lewis The creator of this mess Rated: Expert Hobbies: Computer Architecture and Neural Networking Monica My girlfriend Rated: Fair Hobbies:Hockey, Cooking, and Alien Zapping Dave CE Grad & Friend Rated: Very Good Hobbies: Graphics and Neural Networking Other players: Aaron, Chen, Paul, Greg The players will select what difficulty they feel most comfortable correlations with between and input variables and output difficulty will be made by the neural network.

Progress

• (11/01) Developed Game, Scoring Algorithm, Difficulty Algorithm • (12/4/01) Developed methods for Saving High Score info and Player History • (12/7/01) Lots of game playing • (12/10/01) Changed Matlab code to correct config., realized needed more data