An Exploration of Collision-based Enemy Morphology Generation

Computer Science > Artificial Intelligence [Submitted on 1 Jun 2026] An Exploration of Collision-based Enemy Morphology Generation Johor Jara Gonzalez, Matthew Guzdial Despite a great deal of prior research into Procedural Content Generation (PCG), relatively little prior work has explored generating enemies for video games. In particular, there is almost no work on generating enemy morphologies, the basic body plan or collision information for in-game enemies, despite the existence of related morphology generation work in robotics. In this paper, we explore three different novel approaches to generate enemy morphologies based on player collision information. We found that each approach provides different strengths and weaknesses, but all had equivalent or better performance than an evolutionary baseline adapted from prior robotics morphology work. Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2606.02832 [cs.AI]   (or arXiv:2606.02832v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2606.02832 Focus to learn more Submission history From: Johor Jara Gonzalez [view email] [v1] Mon, 1 Jun 2026 19:52:33 UTC (3,620 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-06 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)