Honey bees must balance effort, risk, and reward, making quick and accurate judgments about which flowers are most likely to provide food for their beehive. Research published in a journal eLife This day reveals how millions of years of evolution have engineered honey bees to make quick decisions and reduce risk.
This study advances our understanding of insect brains, how our brains evolved, and how to design better robots.
This paper presents a model of decision-making in bees and identifies the pathways in their brain that enable them to make quick decisions. The study was led by Professor Andrew Barron from Macquarie University in Sydney, Dr Hadi Mabudi and Neville Dearden and Professor James Marshall from the University of Sheffield.
“Decision making is at the heart of cognition,” says Professor Barron. “This is the result of evaluating possible outcomes, and animal life is full of decisions. A honey bee has a brain smaller than a sesame seed. Yet it can make decisions faster and more accurately than we can. A robot programmed to do the work of a bee would need a backup supercomputer.”
“Today’s autonomous robots operate mostly with remote computing support,” continues Professor Barron. “Drones are relatively brainless, they have to make radio contact with data centers. This path of technology will never allow drones to explore Mars on their own – NASA’s stunning Mars rovers have covered about 75 kilometers in years of exploration.”
Bees must work quickly and efficiently, finding nectar and bringing it back to the hive, while avoiding predators. They need to make a decision. Which flower will have nectar? When they are in flight, they are only vulnerable to air attacks. When landing for food, they are vulnerable to spiders and other predators, some of which use camouflage to look like flowers.
“We trained 20 bees to identify five different colored ‘flower disks’. Blue flowers always contain molasses,” says Dr. Mabodi. Green flowers always contain quinine [tonic water] With a bitter bee taste. Sometimes other colors contain glucose.”
We then introduced each bee to a ‘garden’ where the ‘flowers’ had freshly distilled water. We filmed each bee and then watched the video for over 40 hours, tracking the paths of the bees and calculating how long it took them to make a decision.
“If bees believe a flower is about to get food, they quickly decide to land on it, in an average of 0.6 seconds,” says Dr. MaBouDi. “If they believe the flower will not have food, they make a decision quickly.”
If they weren’t sure, it took them longer—1.4 seconds on average—and that time reflects the possibility of food in the flower.
The team then created a computer model from first principles with the aim of replicating the bees’ decision-making process. They found that the structure of their computer model closely resembled the physical layout of a bee brain.
“Our study demonstrates complex independent decision making with minimal neural circuits,” said Professor Marshall. “We now know how bees make intelligent decisions, and we study how quickly they collect and sample information. We think bees use their flight movements to enhance their visual system to better find the best flowers.”
AI researchers can learn a lot from insects and other “simple” animals. Millions of years of evolution have produced highly efficient brains with very low energy requirements. Professor Marshall, co-founder of Opteran, a company that reverse-engineered insect brain algorithms to allow machines to move autonomously, like nature, says the future of AI in industry will be inspired by biology.
2023-07-10 17:51:37
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