Significance Many real-life decisions where one out of two actions must be chosen can modeled on networks consisting individuals who are either coordinating, that is, take an action only if sufficient neighbors also doing so, or anticoordinating, too many the opposite. It is not yet known whether such tend to reach a state every individual satisfied with his decision. We show indeed any network and anticoordinating always reaches satisfactory state, regardless how they connected, different...

Abstract Most social interactions do not take place at random. In many situations, individuals choose their interaction partners on the basis of phenotypic cues. When this happens, are often homophilic, that is, they tend to interact with similar them. Here we investigate joint evolution cues and cue-dependent strategies. By a combination individual-based simulations analytical arguments, show homophily evolves less easily than earlier studies suggest. The evolutionary interplay cue-based...

Planning forest management relies on predicting insect outbreaks such as mountain pine beetle, particularly in the intermediate-term future, e.g., 5-year. Machine-learning algorithms are potential solutions to this challenging problem due their many successes across a variety of prediction tasks. However, there subtle challenges applying them: identifying best learning models and subset available covariates (including time lags) properly evaluating avoid misleading performance-measures. We...

Abstract Toxic cyanobacterial blooms (CBs) are becoming more frequent globally, posing a threat to freshwater ecosystems. While making long‐range forecasts is overly challenging, predicting imminent CBs possible from precise monitoring data of the underlying covariates. It is, however, infeasibly costly conduct on large scale, leaving most lakes unmonitored or only partially monitored. The challenge hence build predictive model that can use incomplete, partially‐monitored make near‐future CB...

Early Warning Signals (EWSs) are vital for implementing preventive measures before a disease turns into pandemic. While new diseases exhibit unique behaviors, they often share fundamental characteristics from dynamical systems perspective. Moreover, measurements during outbreaks corrupted by different noise sources, posing challenges Time Series Classification (TSC) tasks. In this study, we address the problem of having robust EWS outbreak prediction using best-performing deep learning model...

Accuracy, recall, specificity, and precision are key performance measures for binary classifiers. To obtain these measures, the probabilities generated by classifiers must be converted into deterministic labels using a threshold. Exhaustive search methods can computationally expensive, prompting need more efficient solution. We propose an integer linear programming (ILP) formulation to find threshold that maximizes any combination of measures. Simulations experiments on four real-world...

Reliable angler activity data inform fisheries management. Traditionally, such are gathered through surveys, but an innovative cost-effective approach involves utilizing online platforms and smartphone applications. These citizen-sourced were reported to correlate with conventional survey information. However, the nature of this correlation--whether direct or mediated by intermediate variables--remains unclear. We applied Bayesian networks from Angler's Atlas website, MyCatch application,...

To study how sustainable cooperation might emerge among self-interested interacting individuals, we investigate the long-run behavior of decision-making dynamics in a finite, well-mixed population who play collectively over time game. Repeatedly each individual is activated asynchronously to update her decision either cooperate or defect according myopic best-response rule. The game's payoff matrices, chosen be those prisoner's dilemma snowdrift games underscore cooperation-centered social...

Various populations of interacting decision-making agents can be modeled by asynchronous best-response dynamics or, equivalently, linear threshold dynamics. Building upon recent convergence results in the absence control, we now consider how such a network efficiently driven to desired equilibrium state offering payoff incentives or rewards for using particular strategy, either uniformly targeted individuals. We begin showing that strategy changes are monotone following an increase payoffs...

The timely detection of disease outbreaks through reliable early warning signals (EWSs) is indispensable for effective public health mitigation strategies. Nevertheless, the intricate dynamics real-world spread, often influenced by diverse sources noise and limited data in stages outbreaks, pose a significant challenge developing EWSs, as performance existing indicators varies with extrinsic intrinsic noises. Here, we address modelling when measurements are corrupted additive white noise,...

Abstract Although ecological models used to make predictions from underlying covariates have a record of success, they also suffer limitations. They are typically unable when the value one or more is missing during testing. Missing values can be estimated but methods often unreliable and result in poor accuracy. Similarly, training hinder parameter estimation many models. Bayesian networks handle these other limiting issues, such as having highly correlated covariates. However, rarely their...

Abstract The need for improved models that can accurately predict COVID-19 dynamics is vital to managing the pandemic and its consequences. We use machine learning techniques design an adaptive learner that, based on epidemiological data available at any given time, produces a model forecasts number of reported deaths cases in United States, up 10 weeks into future with mean absolute percentage error 9%. In addition being most accurate long-range COVID predictor so far developed, it captures...

To understand the emergence and sustainment of cooperative behavior in interacting collectives, we perform global convergence analysis for replicator dynamics a large, well-mixed population individuals playing repeated snowdrift game with four typical strategies, which are always cooperate (ALLC), tit-for-tat (TFT), suspicious (STFT), defect (ALLD). The dynamical model is 3-D ordinary differential equation (ODE) system that parameterized by payoffs base game. Instead routine searches...

In anticoordination social contexts such as stock selection, resource allocation, and crowd dispersion, an individual earns more if the opponents adopt her opposite strategy. Based on their experience available information, individuals may either evaluate all options decide most profitable one, or simply mimic successful others. These two types of decision-makers are known best-responders imitators, respectively. Previous studies have shown that in contexts, a population reaches equilibrium...

In both economic and evolutionary theories of games, two general classes evolution can be identified: 1) dynamics based on myopic optimization 2) imitations or replications. The collective behavior structured populations governed by these vary significantly. Particularly in social dilemmas, optimizations typically lead to Nash equilibrium payoffs that are well below the optimum, e.g., <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">the...

For a population of interacting self-interested agents, we study how the average cooperation level is affected by some individuals' feelings being betrayed and guilt. We quantify these as adjusted payoffs in asymmetric games, where for different emotions, payoff matrix takes structure that either prisoner's dilemma or snowdrift game. Then analyze evolution well-mixed each whom associated with such matrix. At time-step, an agent randomly chosen from to update her strategy based on myopic...

This dataset provides information related to the outbreak of COVID-19 disease in United States, including data from each 3142 US counties beginning (January 2020) until June 2021. is collected many public online databases and includes daily number confirmed cases deaths, as well 46 features that may be relevant pandemic dynamics: demographic, geographic, climatic, traffic, public-health, social-distancing-policy adherence, political characteristics county. We anticipate researchers will use...

Stability analysis is presented in this paper to study the evolution of large populations well mixed individuals playing three typical reactive strategies - always cooperate, tit-for-tat and suspicious tit-for-tat. After parameterizing corresponding payoff matrices, we use replicator dynamics, a powerful tool from evolutionary game theory, investigate how population dynamics evolve over time. We show equilibria as their stability properties change for mutual cooperation changes. Both...