Modeling observed natural behavior using fuzzy logic

Eviatar Tron, Michael Margaliot*

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review


In biology, economics, and many other fields of science, human observers have provided linguistic descriptions and explanations of various phenomena. To study these phenomena in a systematic manner, there is a need to construct a suitable mathematical model, a process that usually requires subtle mathematical understanding. In this paper, we propose using the theory of fuzzy logic as a simple, direct, and natural approach to model building, namely, transforming the linguistic description into fuzzy rules and applying fuzzy inferencing to obtain the mathematical model. This approach follows the idea that the real power of fuzzy logic is in its ability to handle and manipulate linguistic information based on perceptions rather than equations. Furthermore, it allows researchers to quickly and intuitively create analytical models from observed behavior and to verify that their linguistically stated explanations indeed yield the observed behavior. We demonstrate this using an example of territorial behavior of fish.

Original languageEnglish
Number of pages5
StatePublished - 2003
EventThe IEEE International conference on Fuzzy Systems - St. Louis, MO, United States
Duration: 25 May 200328 May 2003


ConferenceThe IEEE International conference on Fuzzy Systems
Country/TerritoryUnited States
CitySt. Louis, MO


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