Ralf H. J. M. Kurvers

Foraging is a prime example of adaptive decision-making in uncertain and changing environments. Foragers need to continuously integrate their direct experiences and observations of what others are doing with what they already know about the distribution of prey. Yet little is known about the importance of prior knowledge relative to dynamically sampled information in social foraging settings. Here, we investigated the role of prior beliefs in five large-scale ice-fishing competitions involving 49–53 highly experienced ice-fishers in 251 foraging trips. To quantify their prior spatial beliefs, participants marked areas they believed to have high resource abundance on topographic maps containing isoclines (i.e., depth curves) before each competition. GPS devices and headcams tracked behavioural states and foraging success. We found that prior beliefs about the fish distribution are to a large extent driven by lake topography and therefore converge across individuals. However, these prior beliefs were not systematically linked to foraging success. While prior beliefs predicted spot choices, especially in the beginning of competitions, they were heavily outweighed by dynamic personal and social information sources. Exploring how the use of prior beliefs differed between foraging trips, we found that high reliance on prior beliefs was associated with reduced avoidance of unsuccessful locations which resulted in limited spatial exploration. We conclude that dynamic information sampling and accumulation are key processes in social foraging decisions, with prior spatial beliefs playing only a minor role in natural environments where resources are hard to predict in advance.

Sociality can facilitate the discovery of novel resources, yet it can also entail costs, including increased competition, aggression, sexual harassment and disease transmission. Selection should therefore favour social flexibility as a response to changes in resource conditions, allowing individuals to adjust their social associations optimally. Quantifying these social adjustments and how they allow individuals to benefit in dynamically changing resource environments can provide insight into the adaptive capacity of wild animal populations. We experimentally studied social flexibility in wild guppies Poecilia reticulata by examining their fission–fusion dynamics. Using mixed‐sex sets of individually marked fish, we manipulated recent foraging experience by presenting them with unpredictable, ephemeral food patches or control patches in the wild. Guppies that had been exposed to ephemeral food patches significantly increased their sociality, doubling the proportion of time spent social compared to controls. This shift was driven by both an increase in the probability of starting and a decrease in the probability of ending social contact. Stronger increases in sociality were associated with individuals more often locating ephemeral food patches, mediated by foraging motivation. Importantly, increased sociality was not merely the result of local aggregation, as exposure to ephemeral food patches increased, rather than reduced, spatial activity. Yet, stronger spatial activity did not result in more time spent social. In a second experiment, fish were briefly presented with food patches they could see and smell but not actually consume. Again, fish increased their level of sociality compared to control, indicating that the observed social response was not merely driven by satiation‐related changes in activity budgets. Together, our results highlight the adaptive and dynamic nature of fission–fusion social systems and support the view that wild animals adaptively shape their social environment in response to fluctuations in resource variability.

Hunting for mobile prey is thought to have played a key role in hominin evolution, by providing high-quality nutrition that supported the development of the exceptionally large human brain (1; 2; 3; 4). However, human–prey dynamics remain poorly understood because studies have not yet tracked human foragers and their prey simultaneously. Here, we employ high resolution tracking of groups of human foragers (ice-fishers) and their prey (fish shoals) to study human–prey dynamics. Our results show that foragers adaptively combined personal and social information in deciding where to forage and for how long, closely matching the prey distribution. Prey responded dynamically to human exploitation, showing increased attraction to fishing activity, alongside decreased biting probability. Furthermore, we found that foragers adaptively relied on memory, preferentially returning to areas with high prey presence, particularly when their current return rate was low. Our results show how human foragers overcome the challenges of extracting invisible, mobile and reactive prey by tightly tuning patch-selection, patch-leaving and patch-return decisions to the distribution and behaviour of their prey.

Humans’ abilities for complex social learning and collective adaptation stand out across species. Yet it is largely unknown how people integrate dynamically changing personal and social cues in realistic environments, resulting in collective intelligence or maladaptive behavior. Here, we report an online 3D immersive-reality experiment in which participants ( n = 621) search for and track a mobile resource under realistic visual–spatial constraints. Participants complete the task either alone or in groups of five with different types of social information and resource speeds. Contrasting earlier work, participants in groups outperform solitary individuals, but only when payoff information was available. High-resolution visual field data and movement trajectories reveal that payoff visibility prompts adaptive recalibration of visual information flow, thereby enabling flexible adaptation. Computational models of fine-grained movement decisions and agent-based simulations show that payoff information lets participants dynamically identify and selectively respond to reliable social cues, thus unlocking the group’s collective potential.

Humans collaborating with AI hold the promise of achieving superior outcomes compared to either acting alone (i.e., human–AI synergy). However, the conditions that facilitate such synergy when humans are advised by AI are not well understood. A recent meta-analysis showed that, on average, human–AI combinations do not outperform the better individual agent. We argue that this pessimistic conclusion arises from insufficient attention to human learning in experimental designs. To substantiate this claim, we reanalyzed all 74 studies included in the original meta-analysis and found that most previous research overlooked design features that foster human learning (e.g., outcome feedback to participants). Our reanalysis further revealed that studies providing outcome feedback show tentatively higher synergy than those without outcome feedback. Crucially, feedback paired with AI explanations was associated with positive synergy, while explanations without feedback were associated with negative synergy—suggesting that explanations improve synergy mainly when humans can learn to verify the AI’s reliability through feedback. Our reanalysis suggests that the current literature underestimates the potential of human–AI collaboration because it predominantly relies on paradigms that do not facilitate human learning, thus hindering humans from effectively adapting their collaboration strategies. However, experiments directly varying learning opportunities are needed for stronger, causal conclusions. We advocate for a paradigm shift in human–AI interaction research that explicitly addresses human learning and thus enhances our understanding of and support for successful human–AI collaboration.

Many consequential decisions are made in environments where outcome probabilities are not explicitly described but must be inferred from experience. In most modern environments, this information search takes place in the presence of others. Yet, the role of social influence in experience-based decisions has been largely overlooked, leaving it unclear how personal and social information combine to shape what people sample, when they stop searching, and what they finally choose. Here, we address all three decision stages. In a preregistered study, participants could freely sample two options before making a final choice, either alone (solo condition) or while observing the final choices of their group members (group condition). We developed a modeling framework and show that social influence left sampling unaffected but altered stopping and choice. Participants searched longer when the group was more divided and stopped earlier when the majority choice agreed with their own personal sampling information. Consequently, they drew fewer samples and encountered fewer rare events than solo participants. When choosing, group members copied others' choices only when their personal information was ambiguous. Comparing decision sequences in groups with a solo baseline, complemented with agent-based simulations, showed that this strategy gave rise to mild information cascades, with decisions in groups being more similar to each other than in a solo baseline. Our results reveal how social influence shapes search, stopping, and choice, and how these individual-level decision rules scale up to collective dynamics.

Collective foraging is widespread across the animal kingdom, allowing animals to more effectively discover resources. However, collective foragers need to balance a key trade-off between private exploration and using social information. Social information can come in very distinct forms, ranging from simple positional cues to complex pay-off information. However, how the types of available social cues and environmental volatility shape collective foraging behaviour is not well understood. We address this using a spatially explicit model in which agents track a mobile resource via multi-agent reinforcement learning (MARL). Agents choose between random exploration, private tracking and social attraction. We systematically varied resource volatility and the type of available social cues to analyse their effect on individual and collective behaviour. Our results show that the quality of social information dictates the emerging collective behaviour. Low-quality social cues (e.g. positions and actions) result in a fragile strategy that is effective in stable environments but fails as volatility increases. Conversely, high-quality social information (e.g. pay-offs) enables behavioural diversity: agents selectively copy others and flexibly change between individual tracking or exploration depending on the environmental volatility. Our findings identify the interplay between information quality and ecological context as an important mechanism governing the emergence of distinct forms of collective behaviour from individual decision rules.

Social information shapes how humans learn, decide, and coordinate. Theory predicts that social information is most valuable early in life, but how social information use changes across the lifespan remains poorly understood. Across seven belief-updating experiments with museum samples from Germany and Japan (ages 6–99 years; N = 41,015), we find a robust age-related trajectory: Social information use is highest early in life, drops sharply until late adolescence, and then rises slowly into late adulthood. Participants at all ages used social information most when it was close to their own belief, supported by convergent social inputs, and came from young adults. Female participants used slightly more social information than male participants, and participants from Germany used more social information than those from Japan. Together, these results reveal early-emerging strategic social information use and help explain information flow in age-diverse populations.

The diversity of foraging styles across environments and social systems is a key driver of the success of our species. Yet the human foraging literature is largely observational, since experimental manipulations in situ are difficult. We investigated highly experienced foragers (ice fishers) in situ through direct experimental manipulations: Foragers fished alone or in groups, and participants in groups were incentivised to either compete or cooperate. High-precision GPS tracking and head-camera data recording foraging behaviour, catch success, and verbal communication, combined with cognitive-computational modelling, showed that foragers adaptively integrated socioecological information. Across all conditions, foragers travelled further when unsuccessful; in groups, they also considered the locations of group members when deciding where to go. Cooperative foragers communicated more, and approached others more frequently, but did not outperform competitive foragers. Our study highlights the adaptive nature of human foraging behaviour, demonstrating how group setting and incentive structures shape spatial decision-making and communication strategies.

Predator–prey interactions can drive arms races of complex adaptation and response patterns. While collective behaviour is common as anti-predator behaviour and well understood mechanistically, little is known on predator strategies in the context of collective prey defences. Here, we investigated attack strategies of predatory birds confronted with an effective collective anti-predator behaviour employed by shoals of small freshwater fish (Poecilia sulphuraria). Analysing over 700 attacks revealed that predators face a trade-off: placing attacks in the shoal centre leads to a stronger prey response, which decreases attack frequency but increases chance for success. The causal relationship between attack location and prey-response plasticity was confirmed experimentally through simulated attacks. Predators adjusted their strategies with conspicuous species avoiding the centre, sacrificing optimal attack positions for lower prey responses. A cryptic predator causing overall low-intensity responses favoured central attacks, showing that the magnitude of the prey’s defence is driving predator attack strategies. Additionally, we report priming effects where repeated attacks in spatial proximity intensified the prey’s response, leading to predator species spacing attacks farther apart, suggesting priming counters sequential hunting strategies. We highlight the complex behavioural patterns underlying predator–prey dynamics in the wild, while mechanistic aspects of collective priming prompt interesting future research directions.