The quick-witted insects could be used to develop machines that “think like bees,” according to new research, leading to more efficient systems.
A recent study has shed light on the sophisticated decision-making processes of honeybees — findings that scientists hope could help build better robots and autonomous systems.
Led by Dr. HaDi MaBouDi from the UK-based University of Sheffield and Professor Andrew Barron from Macquarie University in Sydney, the study explored the strategies honeybees use when deciding which flowers to visit for nectar.
"Our findings show that bees are remarkably swift and precise in their decision-making, choosing in a matter of seconds whether a flower will provide food or not," Dr. MaBouDi explained.
"It's fascinating how they use minor variations in color or odor to make these decisions with such a tiny brain and limited number of neurons."
The researchers trained 20 bees to recognize artificial flowers of five different colors, offering either a reward or deterrent, to study their decision-making under controlled conditions.
Bees confidently decided on the flowers providing food in an average of 0.6 seconds — and were just as quick when they did not.
"A honeybee, with a brain smaller than a sesame seed, can make decisions faster and more accurately than we can. A robot programmed to do a bee’s job would need the backup of a supercomputer,” Professor Barron said.
“Our study provides significant insights into designing autonomous machines that can think and navigate as efficiently as bees."
In related work, scientists from the University of Sheffield are also reverse engineering the honeybee brain model created during the experiments to develop the next generation of autonomous technology.
Professor James Marshall, co-author of the study, is the founder of Opteran, a spinoff company working on creating lightweight, low-cost silicon brains that mimic the decision-making process of insects.
"Our research shows how minimal neural circuitry allows bees to make complex autonomous decisions. Their incredibly efficient brains, evolved over millions of years, can inspire the future of AI," Professor Marshall said.
The findings of the research were published in the eLife journal.
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