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Salvage: The Fall was my final year project at Plymouth University. It's a top down shooter that explores the concept of evolutionary game pacing. Each time a game is started the game picks a dataset from the server that will dictate the numbers and placement of enemies. At the end of the game the player rates their game experience and the results are collated. The datasets that are most liked are then bred together using a genetic algorithm to produce a new generation that are then put through the same process.

The idea was to create a game that uses player experience to improve itself, rather than companies having to worry about the minutia of balancing the experience they can use playtesting and beta periods to allow the game to learn player habits and allow the game to tweak itself to find the optimum level of difficulty. Rather than the game's creators releasing patches to improve it, the game can improve itself.

The game self balances each wave by giving the player a random set of powerups, the number dictated by the wave intensity. I was aiming to increase the intensity of the experience without increasing the difficulty. This would mean that the players aren't marking the dataset on difficulty.

Published Mar 31, 2015