Abstract
Fuzzy qualitative simulation combines the features of qualitative simulation and fuzzy reasoning in order to gain advantages from both. However, the output of a fuzzy qualitative simulation process is a behaviour tree which for complex systems will be large. In order to overcome this and permit focussing on preferred behaviours priortisation was developed. In this paper a new prioritisation scheme is presented that makes use of both constraint and temporal information to perform the prioritisation.
| Original language | English |
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| Title of host publication | Proceedings of the IEEE Conference on Fuzzy Systems (Fuzz-IEEE) |
| Place of Publication | Imperial College, London |
| Pages | 1-6 |
| Number of pages | 6 |
| Publication status | Published - Jul 2007 |
Keywords
- Computational efficiency
- Context modeling
- Educational institutions
- Expert systems
- Fuzzy reasoning
- Fuzzy sets
- Fuzzy systems
- Inference algorithms
- Knowledge Based systems
- Set theory