Repeated Interactions Research Articles

Interfaces do Método de Leitura da Paisagem e Sistemas de Informações Geográficas (SIG): contribuições do estudo das Unidades de Paisagem para o ensino-aprendizagem no Ateliê de Projeto Urbano

The interdisciplinary and multiscale methodological approach presented here seeks to understand the biogeophysical support in repeated interactions with society, highlighting the process of socio-spatial production. It outlines the structuring and adaptation of the Landscape Reading method for didactic workshops in Geographic Information Systems, as a result of the GIS research project applied to Landscape Planning developed in (omitted for blind reading). Structuring such method adapted to geotechnology tools and environmental modeling in a GIS environment proved to be of great value for application in Architecture and Urbanism undegraduate courses, which is undergoing an important process of teaching-learning design methodological adaptation, especially in the areas of landscape, urbanism, and urban and regional planning.

The Spillover Effect of Constituency Statutes Along Supply Chains: Evidence From Supplier Commitment

This study examines the spillover effect of constituency statutes along the supply chain. We posit that the enactment of constituency statutes in customer firms’ incorporation states, by removing legal obstacles for customer firms to cater to non-shareholders’ interests, builds suppliers’ trust and cooperation. Consistent with the notion that constituency statutes entice greater trust from suppliers, we find that suppliers make more relationship-specific investments in the supply chain after the enactment of constituency statutes in customers’ states, indicating a greater commitment to the customer. We also show an improvement in customers’ corporate social responsibility performance in the post-constituency-statute period, thus substantiating the claim that the constituency statutes increase customers’ stakeholder orientation. Cross-sectionally, we find the positive effect of constituency statutes on supplier relationship-specific investments is attenuated if the customer and supplier have more repeated interactions in the past, whereas the effect is more pronounced if suppliers produce durable goods. Overall, we provide novel evidence on the spillover of constituency statutes along the supply chain.

Implications of Asymmetric Loss Cone Distribution on Whistler‐Driven Electron Precipitation at Mercury

AbstractMercury has a large loss cone difference in its two hemispheres due to the northward shifted magnetic dipole. The precipitation difference of energetic electrons in both hemispheres is poorly understood. We show that the northern precipitation is 2.5‐times higher than for a symmetric loss cone due to the effects of the enhanced whistler instability at the southern hemisphere with the larger loss cone. Simulations including nonlinear pitch angle scattering by the whistler‐mode waves show rapid (tens of milliseconds) electron flux modulation related to the wave subpacket structures by repeated interactions within a discrete wave element. The difference in the nonlinear whistler instability in the two hemispheres should enhance the electron precipitation, which, along with the direct impact effects of solar wind, contributes to Mercury's surface–magnetosphere coupling. Electrons hitting the planet's surface may be a possible factor in the formation of water through the formation of hydroxyl groups.

Trust in adolescence: Development, mechanisms and future directions

Trust is the glue of society. While the trust we place in close others is crucial for our wellbeing, trust in strangers is important to fulfill needs that families and friends cannot provide. Adolescence is an important phase for the development of trust in strangers, because the social world of adolescents expands tremendously. We provide an overview of the development of trust in adolescence by reviewing studies that used the trust game, an experimental paradigm to measure trust between dyads during monetary exchange. We start from the notion that trust is a form of social reinforcement learning in which prior beliefs about the trustworthiness of others are continuously updated by new information. Within this framework, development in adolescence is characterized by increasing uncertainty of prior beliefs, a greater tolerance of uncertainty, and a greater tendency to seek and use new information. Accordingly, there is evidence for an increase in initial trust and better adaptation of trust during repeated interactions. Childhood psychological and social-economic adversity may impact this development negatively. To further our understanding of these individual differences, we suggest ways in which the trust game can be enriched to capture trust dilemmas that are relevant to youth with diverse backgrounds.

Incentive-Aware Recommender Systems in Two-Sided Markets

Online platforms in the Internet Economy commonly incorporate recommender systems that recommend products (or “arms”) to users (or “agents”). A key challenge in this domain arises from myopic agents who are naturally incentivized to exploit by choosing the optimal arm based on current information, rather than exploring various alternatives to gather information that benefits the collective. We propose a new recommender system that aligns with agents’ incentives while achieving asymptotically optimal performance, as measured by regret in repeated interactions. Our framework models this incentive-aware system as a multi-agent bandit problem in two-sided markets, where the interactions of agents and arms are facilitated by recommender systems on online platforms. This model incorporates incentive constraints induced by agents’ opportunity costs. In scenarios where opportunity costs are known to the platform, we show the existence of an incentive-compatible recommendation algorithm. This algorithm pools recommendations between a genuinely good arm and an unknown arm using a randomized and adaptive strategy. Moreover, when these opportunity costs are unknown, we introduce an algorithm that randomly pools recommendations across all arms, utilizing the cumulative loss from each arm as feedback for strategic exploration. We demonstrate that both algorithms satisfy an ex-post fairness criterion, which protects agents from over-exploitation. All code for using the proposed algorithms and reproducing results is made available on GitHub.

Collusion by mistake: Does algorithmic sophistication drive supra-competitive profits?

A burgeoning literature shows that self-learning algorithms may, under some conditions, reach seemingly-collusive outcomes: after repeated interaction, competing algorithms earn supra-competitive profits, at the expense of efficiency and consumer welfare. This paper offers evidence that such behavior can stem from insufficient exploration during the learning process and that algorithmic sophistication might increase competition. In particular, we show that allowing for more thorough exploration does lead otherwise seemingly-collusive Q-learning algorithms to play more competitively. We first provide a theoretical illustration of this phenomenon by analyzing the competition between two stylized Q-learning algorithms in a Prisoner’s Dilemma framework. Second, via simulations, we show that some more sophisticated algorithms exploit the seemingly-collusive ones. Following these results, we argue that the advancement of algorithms in sophistication and computational capabilities may, in some situations, provide a solution to the challenge of algorithmic seeming collusion, rather than exacerbate it.

SARI: Shared Autonomy across Repeated Interaction

Assistive robot arms try to help their users perform everyday tasks. One way robots can provide this assistance is shared autonomy . Within shared autonomy, both the human and robot maintain control over the robot’s motion: as the robot becomes confident it understands what the human wants, it intervenes to automate the task. But how does the robot know these tasks in the first place? State-of-the-art approaches to shared autonomy often rely on prior knowledge. For instance, the robot may need to know the human’s potential goals beforehand. During long-term interaction these methods will inevitably break down—sooner or later the human will attempt to perform a task that the robot does not expect. Accordingly, in this article we formulate an alternate approach to shared autonomy that learns assistance from scratch. Our insight is that operators repeat important tasks on a daily basis (e.g., opening the fridge, making coffee). Instead of relying on prior knowledge, we therefore take advantage of these repeated interactions to learn assistive policies. We introduce SARI, an algorithm that recognizes the human’s task, replicates similar demonstrations, and returns control when unsure. We then combine learning with control to demonstrate that the error of our approach is uniformly ultimately bounded. We perform simulations to support this error bound, compare our approach to imitation learning baselines, and explore its capacity to assist for an increasing number of tasks. Finally, we conduct three user studies with industry-standard methods and shared autonomy baselines, including a pilot test with a disabled user. Our results indicate that learning shared autonomy across repeated interactions matches existing approaches for known tasks and outperforms baselines on new tasks. See videos of our user studies here: https://youtu.be/3vE4omSvLvc .

Design of Artificial C-Peptides as Potential Anti-HIV-1 Inhibitors Based on 6-HB Formation Mechanism.

The six-helix bundle (6-HB) is a core structure formed during the membrane fusion process of viruses with the Class I envelope proteins. Peptide inhibitors, including the marketed Enfuvirtide, blocking the membrane fusion to exert inhibitory activity were designed based on the heptads repeat interactions in 6-HB. However, the drawbacks of Enfuvirtide, such as drug resistance and short half-life in vivo, have been confirmed in clinical applications. Therefore, novel design strategies are pivotal in the development of next-generation peptide-based fusion inhibitors. The de novo design of α-helical peptides against MERS-CoV and IAVs has successfully expedited the development of fusion inhibitors. The reported sequences were completely nonhomologous with natural peptides, which can provide some inspirations for the antiviral design against other pathogenic viruses with class I fusion proteins. Here, we design a series of artificial C-peptides based on the similar mechanism of 6-HB formation and general rules of heptads repeat interaction. The inhibitory activity of peptides against HIV-1 was assessed by HIV-1 Env-mediated cell-cell fusion assays. Interaction between artificial C-peptides and target peptides was evaluated by circular dichroism, polyacrylamide gel electrophoresis, size-exclusion chromatography, and sedimentation velocity analysis. Molecular docking studies were performed by using Schrödinger molecular modelling software. The best-performing artificial C-peptide, 1SR, was highly active against HIV-1 env-mediated cell-cell fusion. 1SR binds to the gp41 NHR region, assembling polymer to prevent endogenous 6-HB formation. We have found an artificial C-lipopeptide lead compound with inhibitory activity against HIV-1. Also, this paper enriched both N- and C-teminal heptads repeat interaction rules in 6-HB and provided an effective idea for next-generation peptide-based fusion inhibitors against HIV-1.

Gender and cultural differences in the development of reciprocity in young children.

A foundational mechanism underlying human cooperation is reciprocity. In the context of repeated interactions with others, it is not always clear the degree to which in-kind responses reflect responsiveness to partners' prior behaviors ("reactive" responses), an interest unrelated to the partner ("nonreactive" responses), or any combination of the two. To disentangle these two types of responses, we presented children with sequential, one-shot, and costly interactions between themselves and either egalitarian or selfish peers. Study 1 tested direct, generalized, and normative reciprocal scenarios (N = 144 seven-year-old German children; 50% girls and 50% boys), finding that "nonreactive" responses were dominant for boys and manifested in the form of "selfish" resource distribution. Among girls, "reactive" responses were dominant and manifested in the form of in-kind resource distribution. Study 2 addressed even younger German children (N = 144; 4- to 8-year-old German children; 50% girls and 50% boys), exposing the same phenomenon among 4-year-olds, but not among 5.5-year-olds. Study 3 addressed 7-year-old Israeli children (N = 95; 49% girls and 51% boys), and replicated the basic phenomenon, with an additional cultural variation. The early emergence of gender differences in reciprocity and implications are discussed in cultural, socio-developmental, and evolutionary accounts. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Overbidding and heterogeneous behavior in contest experiments:A meta-comment on cross-cultural differences

We revisit the analyses by Sheremeta (2013) and Chowdhury and Moffatt (2017), who pool experimental data from 30 Tullock contests to explain the phenomenon of overbidding. The authors find that the overbidding rate is positively related to the number of contestants and has an inverted U-shaped relationship with the relative endowment. We reuse their data and extend the analysis in the direction of cross-cultural differences, focusing on ethno-linguistic-religious fractionalization as a country-level measure. The results suggest an increased explanatory power of the model, with fractionalization negatively relating to overbidding. In addition, the extended model shows that in the one-shot game the overbidding rate is significantly higher than in the case of repeated interactions. We discuss possible interpretations of our findings.

Friendship Formation in an Enforced Online Regime: Findings from a U.S. University Under COVID

Friendships are a key element of mental health, yet modern life increasingly involves "enforced online regimes," which can inhibit friendship formation. One example is provided by residential university students under COVID-19. Through interviews with 17 graduate students at a U.S. university, we investigate how new friendships were made and maintained under the pandemic. While some of our individual findings echo previous work with online social interaction, our analysis reveals a novel 7-phase friendship formation process that extends Levinger & Snoek's classic pair-relatedness theory. The model enables pinpoint diagnoses. For our participants, three specific phases were blocked -- Physical Awareness (apprehension of another's physical characteristics); Personal Contact (exchange of personal information); and Ongoing Mutuality (repeat interactions to build friendship). The model also explains divergent results under similar but different situations (e.g., residential students under COVID eventually made friends, but students of purely online courses do not), and enables targeted recommendations.

Simulation in New Zealand: what have you done for me lately? New Zealand Association for Simulation in Healthcare (NZASH) white paper.

Medical simulation has become an integral aspect of modern healthcare education and practice. It has evolved to become an essential aspect of teaching core concepts and skills, common and rare presentations, algorithms and protocols, communication, interpersonal and teamworking skills and testing new equipment and systems. Simulation-based learning (SBL) is useful for the novice to the senior clinician. Healthcare is a complex adaptive system built from very large numbers of mutually interacting subunits (e.g., different professions, departments, equipment). These subunits generate multiple repeated interactions that have the potential to result in rich, collective behaviour that feeds back into the organisation. There is a unique opportunity in New Zealand with the formation of Te Whatu Ora - Health New Zealand and Te Aka Whai Ora - Māori Health Authority and the reorganisation of the healthcare system. This viewpoint is a white paper for the integration of SBL into our healthcare system. We describe our concerns in the current system and list our current capabilities. The way SBL could be implemented in pre- and post-registration phases of practice are explored as well as the integration of communication and culture. Interprofessional education has been shown to improve outcomes and is best done with an interprofessional simulation curriculum. We describe ways that simulation is currently used in our system and describe other uses such as quality improvement, safety and systems engineering and integration. The aim of this viewpoint is to alert Te Whatu Ora and Te Aka Whai Ora of the existing infrastructure of the simulation community in New Zealand and encourage them to invest in its future.

Super-additive cooperation

Repeated interactions provide an evolutionary explanation for one-shot human cooperation that is counterintuitive but orthodox1–3. Intergroup competition4–7 provides an explanation that is intuitive but heterodox. Here, using models and a behavioural experiment, we show that neither mechanism reliably supports cooperation. Ambiguous reciprocity, a class of strategies that is generally ignored in models of reciprocal altruism, undermines cooperation under repeated interactions. This finding challenges repeated interactions as an evolutionary explanation for cooperation in general, which further challenges the claim that repeated interactions in the past can explain one-shot cooperation in the present. Intergroup competitions also do not reliably support cooperation because groups quickly become extremely similar, which limits scope for group selection. Moreover, even if groups vary, group competitions may generate little group selection for multiple reasons. Cooperative groups, for example, may tend to compete against each other8. Whereas repeated interactions and group competitions do not support cooperation by themselves, combining them triggers powerful synergies because group competitions constrain the corrosive effect of ambiguous reciprocity. Evolved strategies often consist of cooperative reciprocity with ingroup partners and uncooperative reciprocity with outgroup partners. Results from a behavioural experiment in Papua New Guinea fit exactly this pattern. They thus suggest neither an evolutionary history of repeated interactions without group competition nor a history of group competition without repeated interactions. Instead, our results suggest social motives that evolved under the joint influence of both mechanisms.

Trust and inter-regional M&As: Evidence from China

This paper investigates the economic impact of trust on inter-region mergers and acquisitions (M&As) using a large sample of M&As in China. We find that trust distance among regions negatively predicts frequency of inter-region mergers, merger volume and synergy gains. Economic mechanism analysis shows that trust distance lowers merger gains through imposing transaction cost on the deal. The negative effects of trust distance on inter-region M&As activities and synergy gains are less pronounced when legal institution level distance between regions are smaller, consistent with trust being a substitute for formal institutions; it is less prominent when corporate governance and information disclosure level distance between regions are smaller, suggesting that trust is more important in transactions with higher information asymmetry; it is less salient when financial market development level distances between regions are smaller, consistent with trust is less important with repeated interactions between economic parties. Overall, our results highlight the role trust plays in shaping corporate decisions and economic outcomes.

Impact of committed minorities: Unveiling critical mass of cooperation in the iterated prisoner's dilemma game

The critical mass effect is a prevailing topic in the study of complex systems. Recent research indicates that a committed minority of cooperators, unwavering in their beliefs and consistently maintaining cooperation, can effectively foster widespread cooperation in social dilemma games. However, achieving a critical mass of cooperation in the one-shot prisoner's dilemma requires stricter conditions. The underlying mechanism behind this effect remains unclear, particularly in the context of repeated interactions. This work aims to investigate the influence of a committed minority on cooperation in the iterated prisoner's dilemma game, a widely studied model of repeated interactions between individuals confronting a social dilemma. In contrast to previous findings, we identify tipping points for both well-mixed and structured populations. Our findings demonstrate that a committed minority of unconditional cooperators can induce full cooperation under weak imitation conditions. Conversely, a committed minority of conditional cooperators, who employ extortion strategy, can promote widespread cooperation under strong imitation conditions. These results are consistent across various network topologies and imitation rules, suggesting that critical mass effects may be a universal principle in social dilemma games. Moreover, we discovered that an excessive density of committed extortioners can hinder cooperation in structured populations. This research advances our understanding of the role of committed minorities in shaping social behavior and provides valuable insights into cooperation dynamics. Published by the American Physical Society 2024

The Influence of Internet-Derived Misinformation on Medical Treatment Decisions: A Social Learning Perspective

Purpose “Internet-Derived Information Obstructing Treatment” refers to the phenomenon where patients make their health decisions based on misinformation found online, leading to poor or harmful medical choices. DeGroot’s social learning model is used in this study to enquire at how false information spreads on the internet and influences people’s choices about treatment. We examine how likely patients will choose the wrong treatment, impacting their mental health, such as by making anxiety and depression symptoms worse. In addition, we examine the dynamics of low, high, and mixed levels of influence in the spread of false information. Methods We derived a mathematical framework to analyse the impact of peer-to-peer information sharing on medical decisions using DeGroot’s social learning model by modelling the process of belief updates in digital health networks. Each person’s decision-making is impacted by the views and information they encounter from others; this is known as the multiplier effect of social learning and is incorporated into the model. This method mimics the increasing likelihood that patients will encounter health-related disinformation as they engage with various online communities. Low misinformation influence, high misinformation influence, and mixed initial beliefs were the three scenarios that were modelled in the study. Treatment choices and mental health results were evaluated in light of each scenario. Based on patients’ exposure to false information through internet platforms, the odds ratios (ORs) for negative medical decisions, anxiety, and depression were computed. Results In all of these situations, people were much more likely to make a bad treatment choice when they had incorrect information. Repeated interactions with peers who had been influenced by online false information raised patients’ chances of making bad treatment choices by 50% in the high misinformation scenario (95% confidence interval [CI]: 1.25–1.80). Some patients who were given false information had 40% more anxiety and 35% more depression (OR: 1.40, 95% CI: 1.10–1.70 and OR: 1.35, 95% CI: 1.05–1.65, respectively). According to the model, social learning made false information more powerful, and this was most clear in situations where false information was common. Conclusion DeGroot’s social learning process is a good way to explain how false information found on the internet can affect a patient’s choice of treatment and mental health. Misinformation from the internet can lead to bad medical decisions and higher mental health risks, especially in networks where peers have a lot of power. The results stress the need for targeted interventions to improve digital health literacy and stop the spread of false information in online health communities. Future research should look into ways to stop the social learning processes that keep spreading false information.

False killer whales and fisheries in Hawaiian waters: evidence from mouthline and dorsal fin injuries reveal ongoing and repeated interactions

False killer whales and fisheries in Hawaiian waters: evidence from mouthline and dorsal fin injuries reveal ongoing and repeated interactions

α-Carboxysome Size Is Controlled by the Disordered Scaffold Protein CsoS2.

Carboxysomes are protein microcompartments that function in the bacterial CO2 concentrating mechanism (CCM) to facilitate CO2 assimilation. To do so, carboxysomes assemble from thousands of constituent proteins into an icosahedral shell, which encapsulates the enzymes Rubisco and carbonic anhydrase to form structures typically > 100 nm and > 300 megadaltons. Although many of the protein interactions driving the assembly process have been determined, it remains unknown how size and composition are precisely controlled. Here, we show that the size of α-carboxysomes is controlled by the disordered scaffolding protein CsoS2. CsoS2 contains two classes of related peptide repeats that bind to the shell in a distinct fashion, and our data indicate that size is controlled by the relative number of these interactions. We propose an energetic and structural model wherein the two repeat classes bind at the junction of shell hexamers but differ in their preferences for the shell contact angles, and thus the local curvature. In total, this model suggests that a set of specific and repeated interactions between CsoS2 and shell proteins collectively achieve the large size and monodispersity of α-carboxysomes.

Conflict, cooperation, and institutional choice

Social situations may vary in the severity of conflict between self-interest and collective welfare, and thereby pose collective action problems that might require different institutional solutions. The present study examines the effect of conflict of interests on beliefs, norms, cooperation, and choice of sanctioning institutions in social dilemmas across two experiments (total N = 1304). In each experiment, participants interacted in a public goods game (PGG), and a modified PGG with institutional choice using a 2 (conflict of interests: low vs. high) × 3 (institutional choice: peer punishment/no sanction vs. centralized punishment/no sanction vs. gossip plus ostracism/no sanction) between-participants design. More severe conflict of interests reduces individuals' own cooperation, first-order beliefs about others' cooperation, second-order normative expectations and personal norms of cooperation. This pattern is pronounced over time in repeated interactions. We did not find that conflict of interests influenced the choice to establish a sanctioning institution. Taken together, the challenges arising from stronger conflicting interests can cause the collapse of cooperation, hinder the emergence of trust and norms of cooperation, but do not provide the impetus to support a sanctioning institution to promote cooperation. Implications for solving public goods dilemmas that contain a severe conflict of interests are discussed.

Building Long-Term Human–Robot Relationships: Examining Disclosure, Perception and Well-Being Across Time

While interactions with social robots are novel and exciting for many people, one concern is the extent to which people’s behavioural and emotional engagement might be sustained across time, since during initial interactions with a robot, its novelty is especially salient. This challenge is particularly noteworthy when considering interactions designed to support people’s well-being, with limited evidence (or empirical exploration) of social robots’ capacity to support people’s emotional health over time. Accordingly, our aim here was to examine how long-term repeated interactions with a social robot affect people’s self-disclosure behaviour toward the robot, their perceptions of the robot, and how such sustained interactions influence factors related to well-being. We conducted a mediated long-term online experiment with participants conversing with the social robot Pepper 10 times over 5 weeks. We found that people self-disclose increasingly more to a social robot over time, and report the robot to be more social and competent over time. Participants’ moods also improved after talking to the robot, and across sessions, they found the robot’s responses increasingly comforting as well as reported feeling less lonely. Finally, our results emphasize that when the discussion frame was supposedly more emotional (in this case, framing questions in the context of the COVID-19 pandemic), participants reported feeling lonelier and more stressed. These results set the stage for situating social robots as conversational partners and provide crucial evidence for their potential inclusion in interventions supporting people’s emotional health through encouraging self-disclosure.