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Generating Angry Birds-Like Levels With Domino Effects Using Constrained Novelty Search

This paper proposes a method to generate interesting Angry Birds-like game levels featuring the Rube Goldberg machine (RGM) mechanism using Constrained Novelty Search (CNS). An RGM level in Angry Birds emphasizes a domino effect, which allows it to be completed by only one bird shooting. By evolving the feasible population and infeasible population in CNS, our results show that the entropy of block-type frequencies is higher than the entropy by our previous generator and that two requirements to achieve playable RGM levels – the 100% stability and the perfect-shot rate – are met. The results indicate that the proposed method can generate levels with more diversity than our previous generator while maintaining their playability.