New research reveals bees make better and faster decisions than humans, for the things that matter to them with implications for the future of robot design

Honey bees have to balance effort, risk and reward, making rapid and accurate assessments of which flowers are most likely to offer food for their hive.

The research reveals how millions of years of evolution has engineered honey bees to make fast decisions and reduce risk.

The study enhances our understanding of insect brains, how our own brains evolved, and how to design better robots.

The paper presents a model of decision-making in bees and outlines the paths in their brains that enable fast decision-making.

The study was led by Professor Andrew Barron from Macquarie University in Sydney, Australia, and Dr HaDi MaBouDi, Neville Dearden and Professor James Marshall from the University of Sheffield, UK.

Barron said: “Decision-making is at the core of cognition. It’s the result of an evaluation of possible outcomes, and animal lives are full of decisions.

“A honey bee has a brain smaller than a sesame seed. And yet she can make decisions faster and more accurately than we can.

“A robot programmed to do a bee’s job would need the back up of a supercomputer.”

He added: “Today’s autonomous robots largely work with the support of remote computing.

“Drones are relatively brainless, they have to be in wireless communication with a data centre.

“This technology path will never allow a drone to truly explore Mars solo – NASA’s amazing rovers on Mars have travelled about 75 kilometres in years of exploration.”




Make decisions


Bees need to work quickly and efficiently, finding nectar and returning it to the hive while avoiding predators.

They need to make decisions. Which flower will have nectar? While they’re flying, they’re only prone to aerial attack.

When they land to feed, they’re vulnerable to spiders and other predators, some of which use camouflage to look like flowers.

MaBouDi said: “We trained 20 bees to recognise five different coloured ‘flower disks’.

“Blue flowers always had sugar syrup. Green flowers always had quinine [tonic water] with a bitter taste for bees. Other colours sometimes had glucose.

“Then we introduced each bee to a ‘garden’ where the ‘flowers’ just had distilled water.”

He continued: “We filmed each bee then watched more than 40 hours of video, tracking the path of the bees and timing how long it took them to make a decision.

“If the bees were confident that a flower would have food, then they quickly decided to land on it taking an average of 0.6 seconds.

“If they were confident that a flower would not have food, they made a decision just as quickly.”

If they were unsure, then they took much more time – on average 1.4 seconds – and the time reflected the probability that a flower had food.

The team then built a computer model from first principles aiming to replicate the bees’ decision-making process.

They found the structure of their computer model looked very similar to the physical layout of a bee brain.

Marshall said: “Our study has demonstrated complex autonomous decision-making with minimal neural circuitry.

“Now we know how bees make such smart decisions, we are studying how they are so fast at gathering and sampling information.

“We think bees are using their flight movements to enhance their visual system to make them better at detecting the best flowers.”

AI researchers can learn much from insects and other ‘simple’ animals.

Millions of years of evolution has led to incredibly efficient brains with very low power requirements.

The future of AI in industry will be inspired by biology, says Marshall, who co-founded Opteran, a company that reverse-engineers insect brain algorithms to enable machines to move autonomously, like Nature.

The research is published in eLife.

Both images: Credit: Théotime Colin.

Research Aether / Earth Uncovered