The goal of this thesis is to design, implement and test the explanation-aware case base reasoning system for Warhammer 40k as described in the project of the same name. The system uses object oriented case base reasoning, using JSON as case bases and using general domain knowledge to simulate the Warhammer 40k domain and create armies. Ground work has been laid in for the system to be able to expand its own case base proactively, by learning and simulating armies and battles. The policy was not fully automated due to time and complexity constraints, and manual simulation is a necessary substitute at this time. Explanations are used to to raise confidence in the system and to provide a satisfactory justification of the systems actions. Explanations are also used to instruct new and expert users about the system and the game, both implicitly and explicitly. The paper fully succeeds in fulfilling two out of the three goals it has set out to do and presents the problems with the domain together with the solutions concerning the uncompleted goal. The thesis follows the scientific method and completes it, developing testable predictions, presenting their results and the methods to replicate them. The paper evaluates and discusses the limitations of the domain and implementation, the contributions of the thesis as a whole and the future work to be done.