The horde of nanobots in best-selling novelist Michael Crichton's "Prey" is slowly becoming a reality. It exhibited primitive intelligence in its actions, learning, changing, and interacting with itself to become more powerful.

A new theory developed by a group of researchers at Penn State and motivated by Crichton's book explains how complex structures with signal-processing capabilities emerge in biological or technological systems, enabling the systems to respond to stimuli and carry out useful tasks without external guidance.

The recent publication of the study can be found in Nature Communications.

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A Science Daily story mentioned that Igor Aronson, Huck Chair Professor of Biomedical Engineering, Chemistry, and Mathematics at Penn State, described the narrative of Crichton's book as these tiny nanobots becoming self-organized and self-aware.

Aronson was motivated by the book to investigate how interacting; self-propelled entities may develop collective motion.

Aronson and a group of physicists from the LMU University in Munich have created a new model to explain how biological or synthetic systems construct intricate structures with bare-bones signal-processing capabilities. This model describes how the systems can respond to stimuli and carry out useful tasks independently without the aid of outside forces.

According to Aronson, the discoveries have significance for nanobots and any area that deals with useful, self-assembling materials made of basic building components. Swarms of nanobots, for instance, might be developed by robotics experts to carry out difficult tasks like danger or pollution detection.

Researchers from Penn State and Ludwig-Maximillian University developed a computer model that predicted communications between tiny, self-propelled creatures would result in collective behavior that resembled intellectual activity. The study showed that communications significantly increase a unit's capacity to develop intricate functional states resembling biological systems.

The researchers developed a model to simulate the behavior of social amoebae, single-celled animals that can construct complex structures by exchanging chemical signals. They focused on one particular phenomenon. Cyclic adenosine monophosphate (cAMP), a messenger molecule that the amoebae release when food gets limited, causes the amoebae to congregate and form a multicellular aggregation.

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Future of AIs

No research team has looked at how information processing, on a general level, influences the aggregation of systems of nanobot agents when individual agents-in our example, amoebae-are self-propelled, according to co-author Erwin Frey of Ludwig-Maximilians-Universität München in a statement obtained by Technology Networks.

But researchers said distributed artificial intelligence is now in high demand.

Distributed artificial intelligence, according to Aronson, is practically applicable to any material that has suspended particles that are spread at a tiny scale. It might trigger small electronic circuits in mass-produced microrobots or deliver drugs to the body to treat sickness.

Despite its significance, communication's role in the context of active matter is still largely unknown, according to academics.

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