Current day mobile games often fall into one of two categories, those who want desktop level complexity and thus choose to fill the screen with onscreen buttons, or those that want a simplistic casual experience and thus sacrifice gameplay complexity.

This system adresses this issue and attempts to maintain gameplay compexity, even when controls are simplified to a single touch input.

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The backbone of the system is a neural network which is constructed of in-game scenarios seperated into enemy classes. Meaning each class is evaluated diffently on a per-scenario basis.

By continually learning from how the player fights, the system will pick up on specific behavior such as:

• "The player doesn't want to attack melee enemies when their health is low"
• "The player wants to target a ranged enemy if it is being buffed".

For the players actions to be intentional and meaningful, we need to give the player meaningful decisions to make. In my playtests three enemies each occupy their own specific role in combat. In addition to the different enemy types, other hazards, obstacles, weapons and pickups exist to further complicate the decision making and putting further embhasis on the use of the system.

^{Original designs by Yuting Chen}

With all of these different affordances having the same single input, by design, the systems ability to correctly predict player behavior becomes essential to the experience.

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The ultimate goal of this system is to remove friction between player and game. By creating a more seamless experience, casual mobile players are free to enjoy the relatively limited time in a game-session as compared to similar desktop games.

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For the playtest, I've created an infinately varied playspace for the players to meet every possible combat scenario presented by the combination of arena, enemies and hazards. The level is randomized, not only in terms of layout, but also how and where enemies spawn. Some rooms might have a steady flow of enemies, while other rooms lure you in with a pickup and then surround you with enemies.

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The secondary purpose of using procedural generation is to eliminate the effects of steadily increasing difficulty and the players increace in skill on the playtest data.