Abstract
The invention of mixed reality games that combine virtual and physical play offers a rich and challenging application area for AI techniques.We look at the possibility of using descriptive machine learning to automatically invent simple mixed reality games. Specifically, we demonstrate that the HR learning system can generate coherent domain knowledge from the noisy play data gathered from a number of simple physical games.We describe how this could be used to support mixed reality game invention, and discuss theprospects for further work in this area.
| Original language | English |
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| Title of host publication | Adaptive and Emergent Behaviour and Complex Systems - Proceedings of the 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour, AISB 2009 |
| Pages | 53-58 |
| Number of pages | 6 |
| Publication status | Published - 1 Dec 2009 |
| Externally published | Yes |
| Event | AISB Convention (Society for the Study of Artificial Intelligence and Simulation of Behaviour) 2009 - Edinburgh, United Kingdom Duration: 6 Apr 2009 → 9 Apr 2009 Conference number: 23rd https://web.archive.org/web/20181230191542/http://www.aisb.org.uk/convention/aisb09/index.php |
Publication series
| Name | Adaptive and Emergent Behaviour and Complex Systems - Proceedings of the 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour, AISB 2009 |
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Conference
| Conference | AISB Convention (Society for the Study of Artificial Intelligence and Simulation of Behaviour) 2009 |
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| Abbreviated title | AISB 2009 |
| Country/Territory | United Kingdom |
| City | Edinburgh |
| Period | 6/04/09 → 9/04/09 |
| Internet address |