Explicit Coordination Research Articles

One-dimensional Carrollian fluids. Part I. Carroll-Galilei duality

Galilean and Carrollian algebras acting on two-dimensional Newton-Cartan and Carrollian manifolds are isomorphic. A consequence of this property is a duality correspondence between one-dimensional Galilean and Carrollian fluids. We describe the dynamics of these systems as they emerge from the relevant limits of Lorentzian hydrodynamics, and explore the advertised duality relationship. This interchanges longitudinal and transverse directions with respect to the flow velocity, and permutes equilibrium and out-of-equilibrium observables, unveiling specific features of Carrollian physics. We investigate the action of local hydrodynamic-frame transformations in the Galilean and Carrollian configurations, i.e. dual Galilean and Carrollian local boosts, and comment on their potential breaking. Emphasis is laid on the additional geometric elements that are necessary to attain complete systems of hydrodynamic equations in Newton-Cartan and Carroll spacetimes. Our analysis is conducted in general Cartan frames as well as in more explicit coordinates, specifically suited to Galilean or Carrollian use.

Deliberate synchronization of speech and gesture: effects of neurodiversity and development

Abstract The production of speech and gesture is exquisitely temporally coordinated. In autistic individuals, speech-gesture synchrony during spontaneous discourse is disrupted. To evaluate whether this asynchrony reflects motor coordination versus language production processes, the current study examined deliberately performed hand movements during speech in youth with autism spectrum disorder (ASD) compared to neurotypical youth. Neurotypical adult performance provided a mature baseline. Participants read aloud rhythmic nursery rhymes, while producing a beat-like hand movement. An automated pixel-change video measure identified kinematic peaks; using smoothed acoustic envelope analyses, we identified peaks in speech. Results indicated few diagnostic group differences in explicit speech-movement coordination, although adolescent performance differed from adults. Adults demonstrated higher tempo and greater rhythmicity in their coordination; this group difference suggests that the method is sufficiently subtle to reveal individual differences and that this form of complex coordination undergoes ongoing maturation beyond adolescence. The sample is small, and thus results are necessarily preliminary. In the context of prior speech-gesture coordination studies, these findings of intact synchrony are consistent with the hypothesis that it is the demands of discourse planning, rather than motor coordination, that have led to prior findings of asynchrony during spontaneous speech; this possibility awaits future research.

The Partners of My Partners: Shared Collaborative Experience and Team Performance in Surgical Teams

When teams in organizations are assembled to perform contingent tasks, team members carry with them experiences of prior interaction with partners in different teams. Focal team members share collaborative experiences to the extent that they worked with common external prior partners. Extending current research on team effectiveness, we investigate how shared collaborative experience (SCE) affects team performance. Consistent with the established understanding of team processes as carrying both a teamwork and a taskwork component, we conceptualize SCE as having two distinct dimensions that we call SCE extent and SCE diversity. We posit that high SCE extent increases the ability of teams to refine their teamwork processes, increasing their performance through enhanced coordination and reflexivity. We argue that high SCE diversity hinders the ability of teams to form a shared understanding of task demands, thus undermining team performance. Furthermore, we investigate the contingent effect of task complexity on the relationship between SCE and performance. We argue that the benefits of implicit coordination and the drawbacks of experience diversity decrease as tasks become more complex and require more explicit coordination and wider repertoires of responses. These predictions find support in an analysis of 1343 robot-assisted surgery operations performed by 114 surgeons during a four-year period in a private university hospital. By explicitly recognizing how team members benefit from the network of their shared prior partners, our study contributes to developing a new approach to study the effectiveness of temporary teams in organizations.

The phase space distance between collider events

How can one fully harness the power of physics encoded in relativistic N-body phase space? Topologically, phase space is isomorphic to the product space of a simplex and a hypersphere and can be equipped with explicit coordinates and a Riemannian metric. This natural structure that scaffolds the space on which all collider physics events live opens up new directions for machine learning applications and implementation. Here we present a detailed construction of the phase space manifold and its differential line element, identifying particle ordering prescriptions that ensure that the metric satisfies necessary properties. We apply the phase space metric to several binary classification tasks, including discrimination of high-multiplicity resonance decays or boosted hadronic decays of electroweak bosons from QCD processes, and demonstrate powerful performance on simulated data. Our work demonstrates the many benefits of promoting phase space from merely a background on which calculations take place to being geometrically entwined with a theory’s dynamics.

Sextactic and type-9 points on the Fermat cubic and associated objects

In this note we study line and conic arrangements associated with sextactic and type 9 points on the Fermat cubic F and we provide explicit coordinates for each of the 72 type 9 points on F.

IntrinsicNGP: Intrinsic Coordinate Based Hash Encoding for Human NeRF.

Recently, many works have been proposed to use the neural radiance field for novel view synthesis of human performers. However, most of these methods require hours of training, making them difficult for practical use. To address this challenging problem, we propose IntrinsicNGP, which can be trained from scratch and achieve high-fidelity results in a few minutes with videos of a human performer. To achieve this goal, we introduce a continuous and optimizable intrinsic coordinate instead of the original explicit euclidean coordinate in the hash encoding module of InstantNGP. With this novel intrinsic coordinate, IntrinsicNGP can aggregate interframe information for dynamic objects using proxy geometry shapes. Moreover, the results trained with the given rough geometry shapes can be further refined with an optimizable offset field based on the intrinsic coordinate. Extensive experimental results on several datasets demonstrate the effectiveness and efficiency of IntrinsicNGP. We also illustrate the ability of our approach to edit the shape of reconstructed objects.

Exploring the varying agendas of principals, teachers, and a university related to mentorship

ABSTRACT Teachers are entering the field with a different set of teaching expectations than existing teachers were held to during their own training programs. As a result of shifts in teacher preparation practices and increasingly diverse student populations, existing teachers may not be equipped to mentor novice and student teachers, perpetuating cycles of inequity and frustration. Employing qualitative methods that examined the perspectives of multiple stakeholders, this study explores factors that inform existing teachers’ willingness and ability to mentor the next generation of teachers. Findings suggest that there needs to be more explicit guidance and coordination on the part of all stakeholders, each of whom presents unique perceptions and agendas regarding mentoring the next wave of teachers.

Fiscal policy in times of fiscal stress (or what to do when r > g)

South Africa runs a primary fiscal deficit and the long-term interest rate on government borrowing, r, is greater than the long-term economic growth rate, g. Without intervention, debt will continue to rise until there is a disorderly fiscal stop. Reforms to raise growth have not materialised, leaving fiscal consolidation as the second-best solution. Using a medium-sized, open-economy, fiscal DSGE model of South Africa, we show that the least cost policy is to impose a time-consistent fiscal policy rule with debt-to-GDP as the fiscal anchor and a pre-announced path for government consumption spending as the intermediate operational objective. This result obtains with and without explicit policy coordination between the fiscal and monetary authorities.

Automated construction of cognitive maps with visual predictive coding

Humans construct internal cognitive maps of their environment directly from sensory inputs without access to a system of explicit coordinates or distance measurements. Although machine learning algorithms like simultaneous localization and mapping utilize specialized inference procedures to identify visual features and construct spatial maps from visual and odometry data, the general nature of cognitive maps in the brain suggests a unified mapping algorithmic strategy that can generalize to auditory, tactile and linguistic inputs. Here we demonstrate that predictive coding provides a natural and versatile neural network algorithm for constructing spatial maps using sensory data. We introduce a framework in which an agent navigates a virtual environment while engaging in visual predictive coding using a self-attention-equipped convolutional neural network. While learning a next-image prediction task, the agent automatically constructs an internal representation of the environment that quantitatively reflects spatial distances. The internal map enables the agent to pinpoint its location relative to landmarks using only visual information.The predictive coding network generates a vectorized encoding of the environment that supports vector navigation, where individual latent space units delineate localized, overlapping neighbourhoods in the environment. Broadly, our work introduces predictive coding as a unified algorithmic framework for constructing cognitive maps that can naturally extend to the mapping of auditory, sensorimotor and linguistic inputs.

Explicit coordinated signal control using soft actor–critic for cycle length determination

AbstractExplicit signal coordination carries prior knowledge of traffic engineering and is widely accepted for global implementation. With the recent popularity of reinforcement learning, numerous researchers have turned to implicit signal coordination. However, these methods inevitably require learning coordination from scratch. To maximize the use of prior knowledge, this study proposes an explicit coordinated signal control (ECSC) method using a soft actor–critic for cycle length determination. This method can fundamentally solve the challenges encountered by traditional methods in determining the cycle length. Soft actor–critic was selected among various reinforcement learning methods. A single agent was administered to the arterials. An action is defined as the selection of a cycle length from among the candidates. The state is represented as a feature vector, including the cycle length and features of each leg at every intersection. The reward is defined as departures that indirectly minimize system vehicle delays. Simulation results indicate that ECSC significantly outperforms the baseline methods, as evident in system vehicle delay across nearly all demand scenarios and throughput in high demand scenarios. The ECSC revitalizes explicit signal coordination and introduces new perspectives on the application of reinforcement learning methods in signal coordination.

Thermodynamic Stability Theories of Irreversible Processes and the Fourth Law of Thermodynamics.

Three approaches for determining the thermodynamic stability of irreversible processes are described in generalized formulations. The simplest is the Gibbs-Duhem theory, specialized to irreversible trajectories, which uses the concept of virtual displacement in the reverse direction. Its only drawback is that even a trajectory leading to an explosion is identified as a thermodynamically stable motion. In the second approach, we use a thermodynamic Lyapunov function and its time rate from the Lyapunov thermodynamic stability theory (LTS, previously known as CTTSIP). In doing so, we demonstrate that the second differential of entropy, a frequently used Lyapunov function, is useful only for investigating the stability of equilibrium states. Nonequilibrium steady states do not qualify. Without using explicit perturbation coordinates, we further identify asymptotic thermodynamic stability and thermodynamic stability under constantly acting disturbances of unperturbed trajectories as well as of nonequilibrium steady states. The third approach is also based on the Lyapunov function from LTS, but here we additionally use the rates of perturbation coordinates, based on the Gibbs relations and without using their explicit expressions, to identify not only asymptotic thermodynamic stability but also thermodynamic stability under constantly acting disturbances. Only those trajectories leading to an infinite rate of entropy production (unstable states) are excluded from this conclusion. Finally, we use these findings to formulate the Fourth Law of thermodynamics based on the thermodynamic stability. It is a comprehensive statement covering all nonequilibrium trajectories, close to as well as far from equilibrium. Unlike previous suggested "fourth laws", this one meets the same level of generality that is associated with the original zeroth to third laws. The above is illustrated using the Schlögl reaction with its multiple steady states in certain regions of operation.

“Tacit bundling” among rivals: Limited-availability bargains for loss-averse consumers

This paper derives a stochastic discount strategy that encourages the joint consumption of two partial-substitute goods. The seller of the less valuable product offers a limited-availability discount to consumers with reference-dependent preferences à la Kőszegi and Rabin (2006). The stochastic discount introduces uncertainty in the consumers’ outcomes and increases their willingness to pay. Due to market competition, such stochastic pricing is effective only when it induces consumers to purchase both products. The other seller, who can only use deterministic pricing, tacitly consents as he has no benefit from engaging in a price war. Thus, a collusive outcome – which harms consumer welfare – is achieved without any explicit coordination between the two sellers.

Decentralized Scheduling with QoS Constraints: Achieving O(1) QoS Regret of Multi-Player Bandits

We consider a decentralized multi-player multi-armed bandit (MP-MAB) problem where players cannot observe the actions and rewards of other players and no explicit communication or coordination between players is possible. Prior studies mostly focus on maximizing the sum of rewards of the players over time. However, the total reward maximization learning may lead to imbalanced reward among players, leading to poor Quality of Service (QoS) for some players. In contrast, our objective is to let each player n achieve a predetermined expected average reward over time, i.e., achieving a predetermined level of QoS. We develop a novel decentralized MP-MAB algorithm to accomplish this objective by leveraging the methodology of randomized matching. We prove that our decentralized algorithm can ensure that all players have an O(1) QoS regret. We also reveal an analog between our MP-MAB model and the online wireless queuing systems, which builds a connection between QoS in MP-MAB learning and stability in queuing theory.

How external and agency characteristics are related to coordination in homecare – findings of the national multicenter, cross-sectional SPOTnat study

BackgroundHomecare client services are often distributed across several interdependent healthcare providers, making proper care coordination essential. However, as studies exploring care coordination in the homecare setting are scarce, serious knowledge gaps exist regarding how various factors influence coordination in this care sector. To fill such gaps, this study’s central aim was to explore how external factors (i.e., financial and regulatory mechanisms) and homecare agency characteristics (i.e., work environment, workforce, and client characteristics) are related to care coordination in homecare.MethodsThis analysis was part of a national multicentre, cross-sectional study in the Swiss homecare setting that included a stratified random sample of 88 Swiss homecare agencies. Data were collected between January and September 2021 through agency and employee questionnaires. Using our newly developed care coordination framework, COORA, we modelled our variables to assess the relevant components of care coordination on the structural, process, and outcome levels. We conducted both descriptive and multilevel regression analyses—with the latter adjusting for dependencies within agencies—to explore which key factors are associated with coordination.ResultsThe final sample size consisted of 1450 employees of 71 homecare agencies. We found that one explicit coordination mechanism (“communication and information exchange” (beta = 0.10, p <.001)) and four implicit coordination mechanisms—“knowledge of the health system” (beta = -0.07, p <.01), “role clarity” (beta = 0.07, p <.001), “mutual respect and trust” (beta = 0.07, p <.001), and “accountability, predictability, common perspective” (beta = 0.19, p <.001)—were significantly positively associated with employee-perceived coordination. We also found that the effects of agency characteristics and external factors were mediated through coordination processes.ConclusionImplicit coordination mechanisms, which enable and enhance team communication, require closer examination. While developing strategies to strengthen implicit mechanisms, the involvement of the entire care team is vital to create structures (i.e., explicit mechanisms) that enable communication and information exchange. Appropriate coordination processes seem to mitigate the association between staffing and coordination. This suggests that they support coordination even when workload and overtime are higher.

Coordinating explicit and implicit knowledge for knowledge-based VQA

Pre-trained models often generate plausible looking statements that are factually incorrect because of the inaccurate implicit knowledge contained in the model’s parameters. Related methods retrieve explicit knowledge from the external knowledge source to help improve the prediction performance and reliability. However, these methods often use weak training signals for the retriever, and require the model to make each prediction based on the retrieved knowledge, even when the retrieved knowledge is not reliable or the model can produce better prediction only using its implicit knowledge. Therefore, it is necessary to enable the pre-trained model to actively select more beneficial knowledge for producing better prediction. This work proposes a novel method to help the model to Coordinate Explicit and Implicit Knowledge (CEIK) for the knowledge-based visual question answering (VQA) task, which is an important direction of pre-trained models. Furthermore, a better training signal is proposed for the retriever according to whether the retrieved knowledge can correct the prediction. Experimental results demonstrate the effectiveness of our method.

Analysis of Coordination Mechanisms during Collaborative Problem-Solving on an Interactive Tabletop Display

AbstractCoordination is an important aspect of group work. Previous studies have shown how collocated multi-user interfaces, such as interactive tabletops, support coordination by providing a shared space that enhances workspace awareness. However, only little is known about the coordination processes that occur during problem-solving on such shared devices and how the design of features and interaction techniques can impact coordination behaviour. In this paper we analyse users’ coordination mechanisms during joint manipulation tasks in Orbitia, an interactive tabletop-based problem-solving activity. The proposed design integrates a series of “breaches” seeking to challenge participants’ collaboration by confronting them to different limitations. We report on a case study with five groups of three users (N = 15), jointly solving tasks while facing different challenges related to the activity interface and the environment. By analysing 135 min of video material along with their transcripts, we identified nine different coordination mechanisms that relate to either coordination of information or coordination of actions. By exploring the occurrences of these mechanisms, we found that sharing unsolicited task-relevant information is a common coordination behaviour that can be observed at interactive tabletops, and that with breaches, more explicit coordination in the form of direct requests, orders, or shadowing is used.

Implicit Coordination and Enterprise Architecting Effectiveness

Many organizations have embraced enterprise architecture (EA) as an approach to support business processes and develop and maintain software systems in an efficient and consistent way across the organization. The extant research on EA has focused mostly on technical and governance aspects of EA, which are important, but insufficient to explain whether EA can yield the promised benefits. For EA to succeed, the processes used to conceptualize, design, implement, manage, and change the EA also need to be effective. We refer to this collection of processes as “enterprise architecting”. Our data from qualitative interviews show that effective architecting is the result of well-coordinated EA activities. Our article investigates how two important types of coordination—explicit (i.e., behavioral) and implicit (i.e., cognitive) coordination influence architecting effectiveness. Our study found that implicit coordination is particularly important because it not only influences architecting effectiveness directly, but it also enhances the effects of explicit coordination. More specifically, shared schemas enhance the benefits of governance mechanisms (coordination by plan), whereas common ground enhances the benefits of communication (coordination by feedback). We also uncovered a “self-fueling” recursive effect in which architecting effectiveness further strengthens implicit coordination, generating a beneficial cycle of continual EA improvement.

Exploring multilevel data with deep learning and XAI: The effect of personal-care advertising spending on subjective happiness

International business research often links the cultural and institutional characteristics of countries to the features of the individuals inhabiting these countries. A distinct approach to analyzing such multilevel problems with deep learning and explainable artificial intelligence methods is presented, using country characteristics as explicit spatial coordinates. Deep learning is tolerant of noise and faults and can approximate arbitrarily complex mathematical structures by developing multiple abstractions. An applied example demonstrates the applicability of this approach by exploring the effect of personal-care advertising spending in 27 countries on the subjective happiness of 376,442 individuals, indicating a statistically significant positive effect, albeit with a trivial effect size.

Seeking and sharing information in collective olfactory search

Searching for a target is a task of fundamental importance for many living organisms. Long-distance search guided by olfactory cues is a prototypical example of such a process. The searcher receives signals that are sparse and very noisy, making the task extremely difficult. Information-seeking strategies have thus been proven to be effective for individual olfactory search and their extension to collective search has been the subject of some exploratory studies. Here, we study in detail how sharing information among members of a group affects the search behavior when agents adopt information-seeking strategies as Infotaxis and its recently introduced variant, Space-Aware Infotaxis. Our results show that even in absence of explicit coordination, sharing information leads to an effective partitioning of the search space among agents that results in a significant decrease of mean search times.

Feudal Latent Space Exploration for Coordinated Multi-Agent Reinforcement Learning.

In this article, we investigate how multiple agents learn to coordinate to form efficient exploration in reinforcement learning. Though straightforward, independent exploration of the joint action space of multiple agents will become exponentially more difficult as the number of agents increases. To tackle this problem, we propose feudal latent-space exploration (FLE) for multi-agent reinforcement learning (MARL). FLE introduces a feudal commander to learn a low-dimensional global latent structure that instructs multiple agents to explore coordinately. Under this framework, the multi-agent policy gradient (PG) is adopted to optimize both the agent policy and latent structure end-to-end. We demonstrate the effectiveness of this method in two multi-agent environments that need explicit coordination. Experimental results validate that FLE outperforms baseline MARL approaches that use independent exploration strategy in terms of mean rewards, efficiency, and the expressiveness of coordination policies.