Beyond Rings: Gathering in 1-Interval Connected Graphs

We examine the problem of gathering [Formula: see text] agents (or multi-agent rendezvous) in dynamic graphs which may change in every round. We consider a variant of the [Formula: see text]-interval connectivity model [9] in which all instances (snapshots) are always connected spanning subgraphs of an underlying graph, not necessarily a clique. The agents are identical and not equipped with explicit communication capabilities, and are initially arbitrarily positioned on the graph. The problem is for the agents to gather at the same node, not fixed in advance. We first show that the problem becomes impossible to solve if the underlying graph has a cycle. In light of this, we study a relaxed version of this problem, called weak gathering, where the agents are allowed to gather either at the same node, or at two adjacent nodes. Our goal is to characterize the class of 1-interval connected graphs and initial configurations in which the problem is solvable, both with and without homebases. On the negative side we show that when the underlying graph contains a spanning bicyclic subgraph and satisfies an additional connectivity property, weak gathering is unsolvable, thus we concentrate mainly on unicyclic graphs. As we show, in most instances of initial agent configurations, the agents must meet on the cycle. This adds an additional difficulty to the problem, as they need to explore the graph and recognize the nodes that form the cycle. We provide a deterministic algorithm for the solvable cases of this problem that runs in [Formula: see text] number of rounds.

Leader–follower formation with reduction of the off-tracking and velocity estimation under visibility constraints

This article addresses the time-varying leader–follower formation control problem for nonholonomic mobile robots, under communication and visibility constraints. Although the leader–follower formation control under visibility constraints has been studied, the elimination of the off-tracking effect has not been widely addressed yet. In this work, a new method to eliminate the off-tracking effect, considering the time-invariant formation as a tractor–trailer system, for unknown and circular tractor paths, taking into account the visibility constraints, is proposed. For a time-varying formation with not circular tractor’s path, the proposed method significantly reduces the off-tracking. Only the relative position and the relative orientation, provided by the on board monocular camera, are required. Thus, both the leader robot’s absolute position and the leader robot’s velocities are not needed. Furthermore, to avoid explicit communication among the robots, an extended state observer is implemented to estimate both the translational and the rotational leader’s velocity. In this way, the desired tasks are executed and achieved in a decentralized manner. For a time-varying formation, with constant leader robot’s velocities, the proposed control strategy, based on the kinematic model, guarantees that the formation errors asymptotically converge to the origin. Based on the Lyapunov theory, the stability proof of the formation errors dynamics is shown. Simulation results, considering time-varying leader robot’s velocities, show the efficiency of the proposed scheme.

COVID Compatibility and Risk Negotiation in Online Dating during the COVID-19 Pandemic

We interviewed 31 individuals about their online dating life and behaviors during the COVID-19 pandemic. We use literature on risk and health behaviors to generate four frames for dealing with risk associated with COVID-19 while dating: 1) Unconcerned about Risk, 2) Preliminary Risk Assessment, 3) Active Risk Negotiation, and 4) Risk Aversion. Further, we argue that risk perception causes daters to use implicit and explicit communication about health behaviors to determine COVID compatibility, a state of being in agreement with a partner about how to best minimize risk of contracting COVID-19. Daters want to know that their partner is behaving with similar regard for health guidance and that they are doing their best to keep those in their communities safe. Though daters may transition between frames throughout the course of the pandemic, we use these four frames to identify sets of beliefs, routines, and personal health practices across our sample that have relevance for social scientists, health communication scholars, and health care practitioners.

Self-Enforcing Price Leadership

A dynamic Bertrand-duopoly model where price leadership emerges in equilibrium is developed. In the price leadership equilibrium, a firm leads price changes and its competitor always matches in the next period. The firms produce a homogeneous product and are identical except for the information they possess about demand. The market size follows a two-state Markov process. Market size realizations are observed by one of the firms but not the other. Without explicit communication, price leadership allows firms to jointly approximate monopolistic profits in equilibrium as the market size becomes more persistent provided that firms are patient. In the presence of persistent market dynamics, the informed firm’s price serves as a signal of current and therefore future market conditions. In the proposed price leadership equilibrium, the informed firm could cut prices without being detected, but it does not do so because it would lead the uninformed to also lower their price in the following period.

A Distributed Approach for Autonomous Cooperative Transportation

Autonomous mobile robots have now emerged as a means of transportation in several applications, such as warehouse, factory, space, and deep-sea where direct human intervention is impossible or impractical. Since explicit communication provides a better and reliable way of multi-robot coordination compared to implicit communication, so it is preferred in critical missions, such as search and rescue, where efficient and continuous coordination between robots is required. Cooperative object transportation is needed when the object is either heavy or too large or needs extra care to handle (e.g., shifting a glass table) or has a complex shape, which makes it difficult for a single robot to transport. All group members need no participation in the physical act of transport; cooperation can still be achieved when some robots transport the object, and others are involved in, say, coordination and navigation along the desired trajectory and/or clear obstacles along the path. A distributed approach for autonomous cooperative transportation in a dynamic multi-robot environment is discussed.

Validating a methodology for understanding pedestrian - vehicle interactions: A comparison of video and field observations

The successful deployment of automated vehicles (AVs) will depend on their capacity to travel within a mixed traffic environment, adopting appropriate interaction strategies across different scenarios. Thus, it is important to gain a detailed understanding of the specific types of interactions that are most likely to arise. The overall purpose of this paper was to present a methodology designed to facilitate the systematic observation of pedestrian-vehicle interactions, and to validate its use for both onsite and video based observations. A detailed observation protocol was developed to capture pedestrian and vehicle movement and communication patterns across four interaction phases. Onsite coders completed field observations of 50 pedestrian-vehicle interactions at a UK intersection, while video coders observed the same interactions recorded through a wireless camera mounted on a nearby rooftop. Results show that the observation protocol provides a reliable methodology for capturing patterns of pedestrian-vehicle interactions, with high levels of inter-coder consistency emerging across all categories of codes. A detailed examination of the specific descriptors selected suggests that onsite coding may be particularly beneficial in situations where the aim is to capture any explicit, and perhaps subtle, communication cues, whereas video based coding may be more appropriate in situations where exact sequences of behaviours or measurements of timings are desired. It is anticipated that this type of observation tool will be beneficial for AV developers to increase their understanding of how to interpret the movements of road users, along with increasing knowledge of when implicit and explicit communication techniques should be used.

Gaining insights into organizational communication dynamics through the analysis of implicit and explicit communication

This report in the journal Gruppe. Interaktion. Organisation. Zeitschrift für Angewandte Organisationspsychologie aims at presenting how the analysis of implicit and explicit communication in organizational interaction can advance our insights into and implications for these interactions for research and science. Communication is a central process in modern organizations. Especially recurring forms of interaction in organizations (e.g., meetings or appraisal interviews) are of great importance for personal and organizational success. In these interactions, the communication between the interacting organizational members has a decisive impact on the interactions’ course and outcomes (e.g., satisfaction with the interaction, performance during the interaction). Therefore, the aim of this paper is to present two aspects of communication that are empirically shown to contribute to successful outcomes of organizational interactions. Based on a practical problem, we illustrate the analysis and implications of (1) implicit communication (that is, the use and coordination of unconsciously used function words such as pronouns, articles, or prepositions) and (2) explicit communication (that is, the overarching meaning of a statement). To further illustrate the practical relevance of both communication behaviors, we present empirical insights and their implications for practice. Taking a glance at the future, possible combinations of these communication behaviors, the resulting avenues for future research, and the importance of a strengthened cooperation between research and practice to gain more naturalistic insights into organizational communication dynamics are discussed.

Tacit Collusion on Steroids: The Potential Risks for Competition Resulting from the Use of Algorithm Technology by Companies

Digitalization has a growing impact on everyone’s life. It influences the way consumers purchase products, read online news, access multimedia content, and even meet or interact socially. At the core of digital products lies algorithm technology, decision-making software capable of fulfilling multiple tasks: data mining, result ranking, user matching, dynamic pricing, product recommendations, and ads targeting, among others. Notwithstanding the perceived benefits of algorithms for the economy, the question has been raised of whether the use of algorithms by businesses might have countervailing effects on competition. Although any anti-competitive behavior typically observed in traditional markets can be implemented by this technology, a particular issue highlighted in discussions between researchers and practitioners is the concern that algorithms might foster collusion. Because of their capacity to increase market transparency and the frequency of interactions between competing firms, they can be used to facilitate parallel collusive behavior while dispensing competing firms with the need for explicit communication. Consequently, it is not excluded that algorithms will be used in the years to come to obtain the effects of a cartel without the need to enter into restrictive agreements or to engage in concerted practices. We evaluate the collusion risks associated with the use of algorithms and discuss whether the “agreement for antitrust purposes” concept needs revisiting. The more firms made use of types of algorithms that enable direct and indirect communication between the competitors, the more likely those companies may be considered liable.

Implicit coordination for 3D underwater collective behaviors in a fish-inspired robot swarm

Many fish species gather by the thousands and swim in harmony with seemingly no effort. Large schools display a range of impressive collective behaviors, from simple shoaling to collective migration and from basic predator evasion to dynamic maneuvers such as bait balls and flash expansion. A wealth of experimental and theoretical work has shown that these complex three-dimensional (3D) behaviors can arise from visual observations of nearby neighbors, without explicit communication. By contrast, most underwater robot collectives rely on centralized, above-water, explicit communication and, as a result, exhibit limited coordination complexity. Here, we demonstrate 3D collective behaviors with a swarm of fish-inspired miniature underwater robots that use only implicit communication mediated through the production and sensing of blue light. We show that complex and dynamic 3D collective behaviors—synchrony, dispersion/aggregation, dynamic circle formation, and search-capture—can be achieved by sensing minimal, noisy impressions of neighbors, without any centralized intervention. Our results provide insights into the power of implicit coordination and are of interest for future underwater robots that display collective capabilities on par with fish schools for applications such as environmental monitoring and search in coral reefs and coastal environments.