Evaluating a Cognitive Agent-Orientated Approach for the creation of Artificial Intelligence in StarCraft
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Abstract
In this thesis a cognitive multi-agent system is developed for the real-time strategy game StarCraft: Brood War using GOAL, a language developed at the Delft University of Technology. StarCraft provides various challenges to GOAL that it has not faced before in terms of complexity and quantity of agents. A connector is required for GOAL to interact with StarCraft: the StarCraft-GOAL Environment Connector. In order to provide context for the development stage, this thesis starts by explaining the basics of StarCraft, GOAL and the connector. The development of the bot that will be created, named ForceBot, takes place over the course of four tournaments that serve as milestones and are used to measure the game performance of ForceBot. As the conditions and participants of these tournaments vary, an additional setup for hosting internal test tournaments is established in order to provide a form of testing that remains consistent over the course of the development. Based on the results of tournaments, it can be concluded that the final game performance of ForceBot is above average with regards to existing StarCraft bots. A total of four aspects of GOAL, the language, tools, connector and computational performance, are analysed based on their usage and performance during development, and suggestions for improvements are made accordingly. Among these four aspects, the computational performance is identified as the primary bottleneck for the game performance of GOAL-based StarCraft bots.