Model shows how intelligent behavior can emerge from non-living agents – ScienceDaily

From a distance they looked like clouds of dust. But the swarm of microrobots in Michael Crichton’s bestseller, Prey, organized itself. It acted with rudimentary intelligence, learning, evolving, and communicating with itself to become more powerful.

A new model from a team of researchers led by Penn State and inspired by Crichton’s novel describes how biological or engineered systems form complex structures endowed with signal processing capabilities that allow the systems to respond to stimuli and perform functional tasks without external guidance .

“Basically, these little nanobots become self-organizing and self-aware,” explains Igor Aronson, Huck Professor of Biomedical Engineering, Chemistry and Mathematics at Penn State, explaining the plot of Crichton’s book. The novel inspired Aronson to study the emergence of collective motion between interacting, self-propelled agents. The study was recently published in nature communication.

Aronson and a team of physicists from LMU Munich have developed a new model to describe how biological or synthetic systems form complex structures endowed with minimal signal processing capabilities that allow the systems to respond to stimuli and perform functional tasks without external ones carry out instructions. The findings have implications for microrobotics and all areas involving functional, self-assembled materials made up of simple building blocks, Aronson said. For example, robotics engineers could create swarms of micro-robots capable of performing complex tasks such as scavenging pollutants or detecting threats.

“When we look at nature, we see that many living things depend on communication and teamwork because it increases their chances of survival,” Aronson said.

Conceived by researchers at Penn State and Ludwig Maximilian University, the computer model predicted that communication by small, self-propelled agents leads to intelligent collective behavior. The study showed that communication dramatically expands a single entity’s ability to form complex functional states similar to living systems.

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The team built their model to mimic the behavior of social amoebas, single-celled organisms that can form complex structures by communicating through chemical signals. You have studied one phenomenon in particular. When food becomes scarce, the amoebas release a chemical messenger known as cyclic adenosine monophosphate (cAMP), which causes the amoeba to congregate in one place and form a multicellular aggregate.

“The phenomenon is well known,” said co-author Erwin Frey from the Ludwig Maximilian University of Munich in a press release. “However, no research group has yet investigated how information processing affects the aggregation of agent systems at a general level when individual agents – in our case amoebas – are self-propelled.”

For decades, scientists have struggled to better understand “active matter,” the biological or synthetic systems that convert energy stored in the environment, such as a nutrient, into mechanical motion and self-assemble into larger structures. Individually, the material has no intelligence or functionality, but collectively the material is capable of responding to its environment with a kind of emergent intelligence, Aronson explained. It’s an ancient concept with futuristic applications.

Aristotle formulated the theory of emergence about 2,370 years ago in his treatise Metaphysics. His language is commonly described as “the whole is greater than the sum of the parts”. In the not-too-distant future, Aronson says, exploration of emerging systems could lead to cell-sized nanobots that self-organize inside the body to fight viruses, or swarms of autonomous micro-robots that can coordinate themselves in complex formations without a pilot.

“We usually talk about artificial intelligence as some kind of sentient android with heightened thinking,” Aronson said. “What I’m working on is distributed artificial intelligence. Each element has no intelligence, but once they come together, they are able to react and make decisions together.”

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Aronson explained that there is currently a great demand for distributed artificial intelligence in the field of robotics.

“If you’re designing a robot to be as cheap as possible, you shouldn’t make it too complex,” he said. “We want to build small robots that are very simple, just a few transistors that work together to have the same functionality as a complex machine, but without the expensive, complicated machines. This discovery will open new avenues for active matter applications in nanoscience and robotics.”

Aronson explained that from a practical point of view, distributed artificial intelligence could be used in any type of substance in which microscopically distributed particles are suspended. It could be used in the body to deliver a drug to fight diseases or to activate tiny electronic circuits in mass-produced micro-robots.

“Despite its importance, the role of communication in the context of active matter remains largely unexplored,” the researchers write. “We identify the decision-making machinery of the individual active ingredients as the driving mechanism for the collectively controlled self-organization of the system.”

The other co-authors of the paper are Alexander Ziepke, Ivan Maryshev and Erwin Frey from the Ludwig Maximilian University of Munich. Igor Aronson’s research was supported by the US Department of Energy and the Alexander von Humboldt Foundation.

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