Abstract
Abstract An increasing body of evidence shows that non-human animal languages maybe far more complex than previously assumed. Semantic content in animal alarm calls has been found in the vocalizations of vervet monkeys, some types of ground squirrels, dwarf mongooses, chickens, and Gunnison’s prairie dogs. This paper presents a classification system that provides important evidential support to earlier work on prairie dog communications. It does so using an entirely different system of analysis and a more fully automated experimental procedure. Furthermore, the application of fuzzy logic led to the development of a new system of metrics that can be used to investigate the difficult issues of how information is encoded in animal vocalizations and the level of linguistic complexity of those vocalizations.
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