Experiments involving real and simulated robots suggest that the relationship between physical movement and sensory input could be crucial to developing more intelligent machines.
Tests involving two real and one simulated robot show that feedback between sensory input and body movement is crucial to navigating the surrounding world. Understanding this relationship better could help scientists build more life-like machines, say the researchers involved.
杏吧原创s studying artificial intelligence have traditionally separated physical behaviour and sensory input. 鈥淏ut the brain鈥檚 inputs are not independent,鈥� says Olaf Sporns, a neuroscientist at Indiana University, US. 鈥淔or example, motor behaviour has a role to play in what the body senses from the environment.鈥�
Advertisement
An increasing number of researchers are taking this approach, known as 鈥渆mbodied cognition鈥�, says Sporns. He worked with roboticist Max Lungarella from Tokyo University in Japan, to create experiments that would test the idea.
Red objects
They used a four-legged walking robot, a humanoid torso and a simulated wheeled robot. All three robots had a computer vision system trained to focus on red objects. The walking and wheeled robots automatically move towards red blocks in their proximity, while the humanoid bot grasps red objects, moving them closer to its eyes and tilting its head for a better view.
To measure the relationship between movement and vision the researchers recorded information from the robots鈥� joints and field of vision. They then used a mathematical technique to see how much of a causal relationship existed between sensory input and motor activity.
鈥淲e saw causation of both kinds,鈥� Sporns says. 鈥淚nformation flows from sensory events to motor events and also from motor events to sensory events.鈥� It is an important experimental demonstration of this aspect of embodied cognition, he claims: 鈥淭his work and that of others is now making it more practical and less of a metaphor.鈥�
Similar experiments ought to show the same relationship in animals, he adds, as evolution has produced bodies and brains that work together to understand the world. Such tests would be much harder to carry out, but Sporns says researchers are starting to investigate how it might be done.
Better bots
The experiments could suggest a better way to design and build robots, Sporns adds. Maximising information flow between sensory and motor systems could produce more flexible, capable systems, he says. Experiments involving more simulated robots, 鈥渆volved鈥� using genetic algorithms, suggest this to be a promising approach, he says.
Daniel Polani, who researches artificial intelligence at Hertfordshire University in the UK, also sees promise. 鈥淯sing similar approaches, it should be possible to produce more efficient cognitive systems, like those in nature, without specialising on a particular task鈥� such as movement or vision, he told New 杏吧原创.
Aaron Sloman, another artificial intelligence researcher, at Birmingham University in the UK, says interaction with the environment is vital to intelligence. But he also points out that the human brain is capable of working with concepts not grounded in the physical world.
鈥淭hat is why you can think about a person in Birmingham whom you have never met,鈥� he says, 鈥淗ow does an architect design a new skyscraper, long before there is anything to see, feel, touch, or manipulate?鈥�
Journal reference PLoS Computational Biology (DOI: 10.1371/journal.pcbi.0020144)
