Direct reciprocity facilitates cooperation in repeated social interactions. Traditional models suggest that individuals learn to adopt conditionally cooperative strategies if they have multiple encounters with their partner. However, most existing models make rather strong assumptions about how individuals decide to keep or change their strategies.

They assume individuals make these decisions based on a strategy’s average performance. This in turn suggests that individuals would remember their exact payoffs against everyone else.

In a recent study, researchers from the Max Planck Institute for Evolutionary Biology, the School of Data Science and Society, and the Department of Mathematics at the University of North Carolina at Chapel Hill examine the effects of realistic memory constraints. They find that cooperation can evolve even with minimal memory capacities. The research is published in the journal Proceedings of the Royal Society B: Biological Sciences.

Direct reciprocity is based on repeated interactions between two individuals. This concept, often described as “you scratch my back, I’ll scratch yours,” has proven to be a pivotal mechanism in maintaining cooperation within groups or societies.

While models of direct reciprocity have deepened our understanding of cooperation, they frequently make strong assumptions about individuals’ memory and decision-making processes. For example, when strategies are updated through social learning, it is commonly assumed that individuals compare their average payoffs.

This would require them to compute (or remember) their payoffs against everyone else in the population. To understand how more realistic constraints influence direct reciprocity, the current study considers the evolution of conditional behaviors when individuals learn based on more recent experiences.

Two extreme scenarios

This study first compares the classical modeling approach with another extreme approach. In the classical approach, individuals update their strategies based on their expected payoffs, considering every single interaction with each member of the population (perfect memory). Conversely, the opposite extreme is considering only the very last interaction (limited memory).

Comparing these two scenarios shows that individuals with limited payoff memory tend to adopt less generous strategies. They are less forgiving when someone defects against them. Yet, moderate levels of cooperation can still evolve.

Intermediate cases

The study also considers intermediate cases, where individuals consider their last two or three or four recent experiences. The results show that cooperation rates quickly approach the levels observed under perfect payoff memory.

Overall, this study contributes to a wider literature that explores which kinds of cognitive capacities are required for reciprocal altruism to be feasible. While more memory is always favorable, reciprocal cooperation can already be sustained if individuals have a record of two or three past outcomes.

This work’s results have been derived entirely within a theoretical model. The authors feel that such studies are crucial for making model-informed deductions about reciprocity in natural systems.

How do particles move in turbulent fluids? The answer to this question can be found in a new model presented in a thesis from the University of Gothenburg. The model could help speed up the development of new drugs.

When you stir a glass of water, it is easy to think that any particles in the water will end up in chaos and move completely randomly. But this is not always the case. For example, the so-called active micro-swimmers can move through flow on their own.

Navid Mousavi, a Ph.D. student at the University of Gothenburg, has created a model including various hydrodynamic factors to study how these particles handle and even utilize turbulence.

Micro-swimmers can be biological, such as plankton, or engineered particles such as nanomotors. Plankton contribute to global ecosystems by producing oxygen and they form the basis of the ocean food web.

Free-riding in the current

Navid Mousavi has created new methods for modeling and studying the navigation of micro-swimmers by combining active matter physics with machine learning principles. The thesis finds optimal behaviors for plankton to survive in their turbulent habitat.

“In the model, plankton use local information for navigation, reflecting the real-world conditions that these small swimmers encounter. Unlike previous models where navigation was based on global information,” says Navid Mousavi.

The research also showed that micro-swimmers can utilize the flow to move faster than they can on their own, which is an important insight for both biological and artificial applications.

Another exciting result of the study is the discovery of optimal behavior to avoid high turbulent strain. Surprisingly, it is observed that micro-swimmers tend to swim against the current to keep their position in low-strain regions.

“This behavior seems to be crucial for survival and allows plankton to avoid predators and stay in nutrient-rich zones,” says Navid Mousavi.

Important knowledge for medicine development

All the strategies found were shown to work effectively in several different scenarios, meaning they can be applied to real-life situations.

The results of the study provide important knowledge that has several applications. An example is in medicine, where it could help develop smart micro-swimmers that can deliver drugs directly to specific areas of the body, making treatments more effective. Environmentally, these tiny swimmers could help clean up microplastics from our oceans and contribute to a healthier planet.

“In the future, we will need to validate the model in experiments, both with natural plankton and artificial micro-swimmers,” says Navid Mousavi.

The researchers also plan to investigate more complex models that deal with energy efficiency and the collective behavior of multiple swimmers.

A Chinese probe carrying samples from the far side of the moon returned to Earth on Tuesday, capping a technically complex 53-day mission heralded as a world first.

The landing module of the Chang’e-6 spacecraft touched down at a predetermined site in Inner Mongolia at 2:07 pm (0607 GMT), the China National Space Administration said, hailing the mission a “complete success”.

It comes bearing soil and rocks from the side of the moon facing away from Earth, a poorly understood region that scientists say holds great research promise because its rugged features are less smoothed over by ancient lava flows than the near side.

That means the materials harvested there may help us to better understand how the moon formed and how it has evolved over time.

China’s space agency said the probe was “functioning normally, signaling that the Chang’e-6 lunar exploration mission was a complete success”.

President Xi Jinping said in a congratulatory message that the “outstanding contributions” of the mission command “will be remembered forever by the motherland and the people”, state broadcaster CCTV reported.

Chang’e-6 blasted off from a space center on the island province of Hainan on May 3 and descended into the moon’s immense South Pole-Aitken Basin almost exactly a month later.

It used a drill and robotic arm to scoop up samples, snapped some shots of the pockmarked surface and planted a Chinese flag made from basalt in the gray soil.

On June 4, the probe made the first ever successful launch from the far side in what Xinhua called “an unprecedented feat in human lunar exploration history”.

National pride, misinformation

China’s burgeoning space exploits are a point of pride for the government, and state media outlets launched rolling coverage of the imminent landing on Tuesday morning.

Live images of the landing site showed workers approaching the landing capsule as several helicopters sat nearby on a broad patch of flat grassland.

One worker planted a Chinese flag next to the capsule, enthusiastically unfurling it into the wind.

Xinhua reported Monday that local farmers and animal herders had been evacuated from the area ahead of the touchdown.

“We hope that our country’s space exploration will continue to advance and that our nation will become stronger,” Uljii, a local herdsman, told Xinhua.

But the mission has also sparked a torrent of online misinformation, with some users of the Weibo social media platform seizing on the unfurling of the Chinese flag to push the false claim that Washington faked the Apollo moon landings, AFP Fact Check found.

‘Space dream’

Plans for China’s “space dream” have shifted into high gear under Xi.

Beijing has poured huge resources into its space program over the past decade, targeting ambitious undertakings in an effort to catch up to traditional space powers the United States and Russia.

It has built a space station, landed robotic rovers on Mars and the moon, and become only the third country to send astronauts into orbit.

But the United States has warned that China’s space program masks military objectives and an effort to establish dominance in space.

China aims to send a crewed mission to the moon by 2030 and plans to eventually build a base on the lunar surface.

The United States also plans to put astronauts back on the moon by 2026 with its Artemis 3 mission.

© 2024 AFP