The robot has brain-like neurons grown in the lab and when the cells were electrically stimulated, the machine successfully navigated a small maze.
A technique called ‘physical reservoir computing’ enabled it to make sense of the brain waves and dodge the barriers, researchers said.
Co-author Professor Hirokazu Takahashi said: “These nerve cells, or neurons, were grown from living cells.
“They acted as the physical reservoir for the computer to construct coherent signals.”
It is the first time intelligence has been “taught” to a robot. The signals passed on environmental information as it moved through the maze.
If the AI (artificial intelligence) vehicle veered in the wrong direction or faced the wrong way, neurons in the cell culture were disturbed by an electric impulse. In a series of trials it was continually fed the signals until it accomplished the task.
The circular machine – about three inches in diameter and two inches high – would fit into the palm of your hand.
Prof Takahashi said: “Our work was the proof of concept the brain tissue could be used as a physical reservoir.”
It opens the door to developing machines that solve problems – by thinking like humans.
Prof Takahashi, a computer engineer at the University of Tokyo, said: “These findings suggest goal directed behaviour can be generated without any additional learning by sending signals to an embodied system.
“The robot could not see the environment or obtain other sensory information, so it was entirely dependent on the electrical trial-and-error impulses.”
It is predicted robots will perform most jobs currently done by humans within 50 years.
Prof Takahashi said: “In our demonstration experiment, a living culture was embodied with a vehicle robot to solve a maze task.”
He was inspired by the idea intelligence emerges from a mechanism extracting coherence from a disorganised, or chaotic, state.
Using the principle, the robot triggers a ‘reservoir’ of information that helps it understand and work out a problem.
Prof Takahashi said: “A brain of an elementary school kid is unable to solve mathematical problems in a college admission exam, possibly because the dynamics of the brain or their ‘physical reservoir computer’ is not rich enough.
“Task solving ability is determined by how rich a repertoire of spatio-temporal patterns the network can generate.”
The Japanese team hope the breakthrough will lead to the development of a supercomputer that mimics the human brain.
It also offers hope of shedding fresh light on the brain’s mechanisms – and why diseases like Alzheimer’s and Parkinson’s occur.
Additional reporting by SWNS