Curvity is the new way to control the drone swarms.

  Curvity is the new way to control the drone swarms. 

"Illustration of robots advancing artificial swarm intelligence inspired by the collective behaviors of birds, fish, and bees."(Rude Baguette, “Curvity Controls Robot Interactions”: Researchers Develop New Framework Allowing Robotic Swarms to Mimic Bird and Fish Group Behaviors)

Drone swarms could be the tool that can make almost everything. The idea is that drones can cooperate and connect their computing capacity when they must make complex decisions. Then the swarm can share missions to individual drones. When we think about robot swarms that can mimic things like bird swarms, those robots must know their position in the swarm. The answer to that question can be curvature or curvity. Rude Baguette tells the next things about curvity. 

“A key innovation of the study is the introduction of a new quantity termed “curvity.” This intrinsic charge-like quality allows a robot to curve in response to external forces, guiding its interactions with fellow robots. Each robot is assigned a positive or negative curvity value, which determines its behavior within the swarm. This innovative approach allows for the collective behavior of the swarm to be controlled, whether it involves flocking, flowing, or clustering.”  (Rude Baguette, “Curvity Controls Robot Interactions”: Researchers Develop New Framework Allowing Robotic Swarms to Mimic Bird and Fish Group Behaviors)

Assistant Professor Stefano Martiniani from New York University emphasized the potential of this approach: “This curvature drives the collective behavior of the swarm, potentially controlling whether the swarm flocks, flows, or clusters.” Such a model transforms the challenge of controlling swarms from complex programming into a material science issue, opening new avenues for research and application.” (Rude Baguette, “Curvity Controls Robot Interactions”: Researchers Develop New Framework Allowing Robotic Swarms to Mimic Bird and Fish Group Behaviors)

Sharing the system into substructures that mimic galactic groups makes it easier to create programs for robots. Each layer or level acts as one robot. 

The system can involve the next type of information. 

“You are a robot of robot group 9. Robots 1 and 2 must be ahead of you. And robot 4 must be on the left side of you. Together, you are Robot Swarm 2, and Swarms 1 must be on your side, and Swarms 3 and 4 must be behind you. Together, your place is in layer 3. That layer must be between layer 2 and 4.” Then the system has other algorithms that tell what to do if one drone is lost. 

The key question is how the robot can determine its position within the swarm. In this case, the modular structure is the solution. There can be multiple data levels, which makes the data structure operate as a mosaic. Or, rather, we can say that the structure mimics the universe. There are individual drones that are galaxies in galactic clusters. Then those drone clusters form a local cluster. Then, local clusters form a super cluster. And then the superclusters form a global cluster. Those clusters are the drone swarms. The ability to share the groups into subgroups makes it easier to program those drones. 

The idea is that the drones can form three or four drone groups. The individual drone knows. What drones are behind it, and what drones are ahead of it? The drone group acts like one drone. And then it must know what drone group is ahead and behind it. Then the drone group must know. Whether it should be above or below some of the other drones. The system can make that quite easily. It can share the drone swarm into layers. And those drones know their own layer. And then they know what drones should be below and what should be above it. Those drones can operate in squares. That can look like randomly changing forms. 

https://www.rudebaguette.com/en/2025/09/curvity-controls-robot-interactions-researchers-develop-new-framework-allowing-robotic-swarms-to-mimic-bird-and-fish-group-behaviors/

How to simulate the entire universe using a laptop?

   How to simulate the entire universe using a laptop? 

How to simulate the entire universe using a laptop? And can psychohistory be possible? 

The idea is this. If we want to simulate a large entirety, we must not have high accuracy. If we want to make a simulation about. How a river flows, we can use the entire river as a model. We must not care. About how a single water molecule or subatomic particle behaves. We must only know where the river flows. To make a prediction about how the river will flow, we must only know where the softest rock is to predict the channel that the river will choose. In meteorology, supercomputers can make very good predictions. If they know the forces that affect the air. In those cases, the system. Look at the entirety. It doesn’t try to make a precise and highly accurate model of how a single water droplet interacts. The system observes the large entireties. Like cloud groups to make a model, how the air mass will behave. 

Weather satellites and computers are good tools. To predict how large hurricanes behave. But those systems are helpless. When they must try to predict how tornadoes will form. Tornadoes are smaller but more destructive than large tropical storms. Tornadoes are too small for weather satellites.

Maybe. The same programs can make predictions of tornadoes. If the system uses so-called atmospheric satellites that observe smaller areas but with higher accuracy. Those systems will get information from smaller areas. But they can use similar computer systems. Researchers used to make a large-scale weather forecast. In this case, it's easy to make a planet-scale weather forecast. But those forecasts are inaccurate. 

In the same way, it's easy to make predictions about how large gas mass behaves. The system removes unnecessary accuracy and handles things like galaxies as solid forms. Those are like pins in the large system. Or maybe we should say that galaxies are like wheels. Those wheels move wave movement, fields, and large material masses over the universe. 

That means if we make inaccurate, “about” predictions. About how large gas masses are. Like galactic superclusters behave, we can make that prediction using laptop computers. In an inaccurate model, we can think that galactic superclusters are the wheels, and the universe is like a ball around those wheels. When the system starts to simulate how the galaxies behave in a local cluster. The system uses the local cluster as a scale, and galaxies are wheels. When the system makes a model of how a galactic supercluster behaves, the local clusters are the wheels. And the last version is the universal scale. The galactic superclusters are the wheels. In the large-scale simulations. The system doesn’t notice or filter out too small actors that have no visible effect on the system. 

This system is called. A variable scale model. The idea is similar to the U.S map. If we want to look at the overview of the weather over the USA. We can use the USA as a whole. But if we want to see what the weather is over in Montana. We can take a Zoom image of the state of Montana. We can use the same computer algorithms in that area. As in larger-scale images. But the higher accuracy means that we lose the entirety. 

Ludwig Boltzmann (1844-1906), Austrian physicist

Can the psychohistory turn true? 

There is a possibility that the same models. Those used for simulating the universe can be used to predict how humans behave. That is called psychohistory. In the SciFi series: “The Foundation”. The idea is that the system predicts the behavior of large human groups. The system uses large human groups. And things like their states’ influence as variables that can predict how people behave. The system makes models. Using billions of people. But if that thing is possible. The system can use the same algorithms for smaller groups. 

In psychohistory, the system looks at things. That happened in the past. Then the system searches for what those things caused. And then. The system searches for details of similar events from its environment. Because people with similar personalities should behave in similar ways in similar situations. So, the system must know. How many certain types of personalities live in an area that faces certain changes? We can think. Human groups have a certain social or psychological mass, and if a certain number of people start behaving in certain ways. That psychological mass can start to pull other people with it, only if it's large enough.

The thing that causes panic is that a certain number of people in a group start to panic. When we think that four people start to panic, that might not seem like a very big thing. But if there are 10 people in one room. And there is one square meter of space. For each person. Then four people will get the larger effect. And one of those reasons is that. There is no outside effect that can suppress the panic effect. And that makes it stronger. If the head of state goes into panic, that can escalate into a very large group. If one single person goes into panic, that has no such effect. 

And then to psychohistory: can we predict how people or nations behave? Every person. With a certain personality. Behaves in certain ways. The thing that makes predictions hard. Is that. We should know. What a person’s personality is. And that’s impossible if the researchers don’t know the entire personal history of the person. 

We can take the scale of millions or billions of people. When we think about psychology and economics. There are inaccuracies. The reason for those inaccuracies is that we don’t know every person’s background. People’s experiences model our behavior. Psychological models are almost right. And they work with most people. But those models are not working with people. Whose nature is not known. We don’t know what type of humans they are if we don’t know that person’s complete history. The personality is unknown, if there is something hidden in history. 

But there should be a certain number of  non-predicted cases. Or a certain type of standard deviation  of cases that behave in a non-predictable way. This means that large, scalable surprises are not very common cases. in large-scale models. Cases like the Kennedy assassination are very rare. They are like black swans, possible but extremely rare things. There must be an acceptable  error level in all models. Some of those black swans can be predicted. We can calculate the possibilities of asteroid hits, but there is a possibility. That some asteroids can come through the defense. Sometimes asteroids are seen. Only when they pass Earth and those things cause problems. 

https://scitechdaily.com/scientists-just-found-a-way-to-simulate-the-universe-on-a-laptop/

https://en.wikipedia.org/wiki/Boltzmann_constant

https://en.wikipedia.org/wiki/Ludwig_Boltzmann

https://en.wikipedia.org/wiki/Psychohistory

https://en.wikipedia.org/wiki/Standard_temperature_and_pressure