High Precision Battle Simulation for Strategy Games


Game AI

Project proposed & supervised by

Simon Lucas, Diego Pérez-Liébana

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- Industry -

High Precision Battle Simulation for Strategy Games

Project proposal abstract:

Many strategy games feature complex battles among different factions where armies, made up of units with different qualities, fight each other with different goals, from taking over enemy settlements, defeating the opponent’s army in the battlefield or defending specific areas of interest.

Being able to simulate the progression and outcome of these battles in advance is a challenging task, but it would be useful for AI and players alike. A precise battle auto-resolver could provide players with the possibility of producing believable battle results in a simulation, and AI players could use it to determine how likely is that the battle turns out in their favour.

The goal of this project is to investigate how to build a model for a precise and fast battle simulator from past played battles, which can be used to provide insights and more personalized predictions based on the player’s play style and army  composition. The simulation should provide instantaneous battle results and details such as how many units were killed or captured on both sides and how much damage each unit took. It should also balance between overly favourable or very unfavourable outcomes, represent basic playing strategies, and take into account highly valued units, arbitrary priorities of the armies, different battle scenarios and the types of units involved.

Academic Supervisors: Simon Lucas (QMUL), Diego Perez-Liebana (QMUL)

Based at:

This is an industry-led project proposed by iGGi partners 

Creative Assembly