Abstract
In this paper, an approach is advocated to use a hybrid approach towards learning behaviour for computer generated entities (CGEs) in a serious gaming setting. Hereby, an agent equipped with cognitive model is used but this agent is enhanced with Machine Learning (ML) capabilities. This facilitates the agent to exhibit human like behaviour but avoid an expert having to define all parameters explicitly. More in particular, the ML approach utilizes co-evolution as a learning paradigm. An evaluation in the domain of one-versus-one air combat shows promising results.
| Original language | English |
|---|---|
| Pages (from-to) | 120-129 |
| Journal | Lecture Notes in Computer Science |
| Volume | 8482 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2014 |
| Event | 27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems - Duration: 3 Jun 2014 → 6 Jun 2014 |
Bibliographical note
Proceedings title: Modern Advances in Applied IntelligencePublisher: Springer International Publishing
ISBN: 978-3-319-07466-5
Editors: M Ali, JS Pan, SM Chen, MF Horng
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Cite this
Wilcke, W. X., Hoogendoorn, M., & Roessingh, J. J. M. (2014). Co-evolutionary Learning for Cognitive Computer Generated Entities. Lecture Notes in Computer Science, 8482(2), 120-129. https://doi.org/10.1007/978-3-319-07467-2_13