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The Role of Learning in the Honey Bee Waggle Dance

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The honey bee “waggle dance” is well known as the method that the bees use to communicate to other members of a hive information about the location of food sources as well as potential nest locations. The information includes direction, distance, and food quality. Ethologists James and Carol Gould call the waggle dance, “the second most information-rich exchange in the animal world,” meaning second only to human language.1

A new study in Science Magazine has determined that in addition to the basic behavior being innate (programmed), there is also a learning element.2 As described in my book Animal Algorithms, “The duration of the dance conveys the distance of the source, where one waggle run (in the figure eight) signifies a standard distance, which varies between five and fifty yards, depending upon the species.”3 Studies have found that the determination of distance is based on optic flow, the progression of objects across the animal’s visual scene.4While the distance calibration varies with species, it does remain remarkably constant. 

Interpreting the Distance

However, it is still unclear how bees that interpret the distance associated with the dance translate that to the behavior controlling travel distance. This new study concludes that the distance calibration, as well as the directional component, requires fine-tuning through learning. Both learning mechanisms occur when young bees observe older experienced bees (termed social learning) as they forage and perform the waggle dances. Experiments demonstrated that the accuracy of both direction and distance improved over time through this social learning method.

A Unique Feature

Social learning is common among many animal species. A good example occurs in songbirds, where young birds learn from adults to perform species-specific songs. In that case the basic melodies of the songs are innate, but performance improves as the birds hear adults. Bees have also been shown to be capable of learning other types of complex behaviors. One study demonstrated that they could learn by observing a demonstration of how to move balls in order to obtain a reward. One thing that was unique about this was that the behavior is not one bees naturally perform. The authors of the study concluded, “That bees solved this novel, complex goal-directed problem — and solved it via observation and using a better strategy than originally demonstrated — shows an unprecedented degree of behavioral flexibility in an insect.”5 Very impressive for animals that have brains containing only about one million neurons.

It must be noted that learning is also largely a programmed behavior, governed by a type of algorithm, particularly for animals with limited cognitive ability. The general mechanism for learning is based on the concept of feedback, where a desired output is compared to a current value, which is then adjusted based on the difference. In the case of the honey bee waggle dance young bees must observe an experienced bee’s flight and dance, encode this information in the brain, compare it to innate programming, and finally compute and adjust the calibration as necessary. Again, this is an algorithmic process, all of which is the product of design.

Notes

  1. James L. Gould and Carol Grant Gould, Nature’s Compass: The Mystery of Animal Navigation (Princeton U. Press, 2012, 77).
  2. “Social signal learning of the waggle dance in honey bees,” Dong et al., Science 379, 1015-1018, 10 March 2023. 
  3. Eric Cassell, Animal Algorithms (Discovery Institute Press, 2021, 60).
  4. “Honeybee Navigation: Nature and Calibration of the ‘Odometer,’” Srinivasan et al., Science 287, 851-853, 4 February 2000.
  5. “Bumblebees show cognitive flexibility by improving on an observed complex behavior,” Loukola et al., Science 355, 833-836, 24 February 2017.

Eric Cassell

Eric Cassell is the author of Animal Algorithms: Evolution and the Mysterious Origin of Ingenious Instincts and is an expert in navigation systems, including GPS. He has had a long-time interest in animal navigation. He has more than four decades of experience in systems engineering related to aircraft navigation and safety. He has served as an engineering consultant for NASA and the Federal Aviation Administration (FAA); has developed computer algorithms for safety systems; and has published numerous technical papers. His academic training includes bachelor’s degrees in biology (George Mason University) and electrical engineering (Villanova University), and a master’s in science and religion from Biola University, which included the history and philosophy of science.
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