Pursuit Behavior Research Articles

The evolution of cooperative chasing on complex networks via a game-based chasing rule

Cooperative pursuit, which involves a set of multiple agents with combined effort to capture some target, is a typical kind of collective intelligent behavior in social populations. It is intriguing how autonomous agents communicate and interaction with each other to facilitate collaborative pursuit tactics. In this paper, we consider the scenario of a set of cops to capture a robber on complex networks. A game-based chasing rule is proposed to coordinate the action of cops. It is shown that cooperative pursuit behavior, such as encirclement, can be generated by the proposed game-based chasing rule. Through experiments on different kinds of networks, it is shown that the game-based chasing rule greatly reduces the required capture time, compared to that of independent chasing rule. This study provides new insight into the development of more sophisticated pursuit and evasion behaviors in complex environments.

Unwanted Pursuit Behavior Victimization as a Predictor of Engagement in Nonsuicidal Self-Injury.

While prior research has studied associations between child abuse and nonsuicidal self-injury (NSSI), there is limited research assessing unwanted pursuit behavior (UPB) victimization and NSSI. In addition, few studies have assessed the self-reported functions of NSSI among survivors of violence. Among a sample of 18-25-year-old young adults (N = 333), both UPB victimization and child abuse were significantly associated with NSSI frequency. In regression models, UPB victimization was associated with increased use of affect regulation, antidissociation/feeling-generation, self-punishment, and antisuicide functions, while child abuse was associated only with antidissociation/feeling-generation and self-punishment. Affect regulation mediated the association between UPB victimization and NSSI frequency, but not the association between child victimization and NSSI frequency. Implications for research and clinical practice will be discussed.

“Some Handle It in Ways Others See as Insane:” College Individuals’ Meaning-Making about their Motivations for Severe Unwanted Pursuit Behaviors

“Some Handle It in Ways Others See as Insane:” College Individuals’ Meaning-Making about their Motivations for Severe Unwanted Pursuit Behaviors

Artificial Intelligence: Arguments for Catastrophic Risk

AbstractRecent progress in artificial intelligence (AI) has drawn attention to the technology's transformative potential, including what some see as its prospects for causing large‐scale harm. We review two influential arguments purporting to show how AI could pose catastrophic risks. The first argument — the Problem of Power‐Seeking — claims that, under certain assumptions, advanced AI systems are likely to engage in dangerous power‐seeking behavior in pursuit of their goals. We review reasons for thinking that AI systems might seek power, that they might obtain it, that this could lead to catastrophe, and that we might build and deploy such systems anyway. The second argument claims that the development of human‐level AI will unlock rapid further progress, culminating in AI systems far more capable than any human — this is the Singularity Hypothesis. Power‐seeking behavior on the part of such systems might be particularly dangerous. We discuss a variety of objections to both arguments and conclude by assessing the state of the debate.

Public Perception of Green Supply Chains and Its Impact on Customer Behavior: An Empirical Analysis

The public is increasingly becoming aware of environmental challenges and adjusting its purchasing behavior in pursuit of sustainable products and services. To compete in the global scene, firms need to transform their supply chains to adhere to eco-friendly practices. This study focuses on the electronics market, which is distinctively interesting due to its small product life cycles, high-end capabilities, and fierce competition. A novel research model comprising nine hypotheses that attempt to investigate and assess the factors influencing customers’ perceptions and purchasing preferences in relation to green supply chains in the electronics industry was developed. We conducted field research to test the model empirically using survey data from 147 individuals with different backgrounds. The dataset was verified and validated by means of explanatory factor analysis. Structural equation modeling analysis was performed that revealed the linkage between demographics (age), willingness to pay, purchasing intention, and green consumerism. Other research findings included the intricate interconnections between environmental concern, knowledge, attitude, customers’ perceptions/effectiveness, and behavior. This research gives insights into green consumerism in the electronics sector, and its managerial implications can guide sustainable supply chain practices and customer-centric marketing approaches.

Objects guide human gaze behavior in dynamic real-world scenes.

The complexity of natural scenes makes it challenging to experimentally study the mechanisms behind human gaze behavior when viewing dynamic environments. Historically, eye movements were believed to be driven primarily by space-based attention towards locations with salient features. Increasing evidence suggests, however, that visual attention does not select locations with high saliency but operates on attentional units given by the objects in the scene. We present a new computational framework to investigate the importance of objects for attentional guidance. This framework is designed to simulate realistic scanpaths for dynamic real-world scenes, including saccade timing and smooth pursuit behavior. Individual model components are based on psychophysically uncovered mechanisms of visual attention and saccadic decision-making. All mechanisms are implemented in a modular fashion with a small number of well-interpretable parameters. To systematically analyze the importance of objects in guiding gaze behavior, we implemented five different models within this framework: two purely spatial models, where one is based on low-level saliency and one on high-level saliency, two object-based models, with one incorporating low-level saliency for each object and the other one not using any saliency information, and a mixed model with object-based attention and selection but space-based inhibition of return. We optimized each model's parameters to reproduce the saccade amplitude and fixation duration distributions of human scanpaths using evolutionary algorithms. We compared model performance with respect to spatial and temporal fixation behavior, including the proportion of fixations exploring the background, as well as detecting, inspecting, and returning to objects. A model with object-based attention and inhibition, which uses saliency information to prioritize between objects for saccadic selection, leads to scanpath statistics with the highest similarity to the human data. This demonstrates that scanpath models benefit from object-based attention and selection, suggesting that object-level attentional units play an important role in guiding attentional processing.

Social Reactions to Disclosures of Intimate Partner Stalking and Unwanted Pursuit Behaviors: Associations With PTSD, Academic Outcomes, and Empowerment.

Among college survivors of unwanted pursuit behaviors (UPBs; 40.1%, n = 189) or intimate partner stalking (IPS, i.e., UPBs causing emotional distress; 32.1%, n = 151), the present study examined effects of social reactions to disclosures on post-traumatic stress disorder (PTSD) symptomatology, academic outcomes, and personal empowerment. Compared to UPB survivors, IPS survivors were more likely to disclose and reported higher positive and negative reactions to disclosure as well as greater frequency of UPBs/IPS, IPV, and PTSD symptoms. Among both groups, only negative social reactions were positively associated with PTSD symptoms. However, among IPS (but not UPB) survivors, only positive social reactions were related to academic outcomes and empowerment when controlling for PTSD and IPS frequency. Implications for research and practice are discussed.

Guidance strategy of motion camouflage for spacecraft pursuit-evasion game

This work is inspired by a stealth pursuit behavior called motion camouflage whereby a pursuer approaches an evader while the pursuer camouflages itself against a predetermined background. We formulate the spacecraft pursuit-evasion problem as a stealth pursuit strategy of motion camouflage, in which the pursuer tries to minimize a motion camouflage index defined in this paper. The Euler-Hill reference frame whose origin is set on the circular reference orbit is used to describe the dynamics. Based on the rule of motion camouflage, a guidance strategy in open-loop form to achieve motion camouflage index is derived in which the pursuer lies on the camouflage constraint line connecting the central spacecraft and evader. In order to dispose of the dependence on the evader acceleration in the open-loop guidance strategy, we further consider the motion camouflage pursuit problem within an infinite-horizon nonlinear quadratic differential game. The saddle point solution to the game is derived by using the state-dependent Riccati equation method, and the resulting closed-loop guidance strategy is effective in achieving motion camouflage. Simulations are performed to demonstrate the capabilities of the proposed guidance strategies for the pursuit–evasion game scenario.

A conceptual framework for how structural changes in emerging acute substance use service models can reduce stigma of medications for opioid use disorder.

Stigma toward people taking medication for opioid use disorder (MOUD) is prevalent, harmful to the health and well-being of this population, and impedes MOUD treatment resource provision, help-seeking, and engagement in care. In recent years, clinicians have implemented new models of MOUD-based treatment in parts of the United States that integrate buprenorphine initiation into emergency departments and other acute general medical settings, with post-discharge linkage to office-based treatment. These service models increase access to MOUD and they have potential to mitigate stigma toward opioid use and MOUD. However, the empirical literature connecting these emerging service delivery models to stigma outcomes remains underdeveloped. This paper aims to bridge the stigma and health service literatures via a conceptual model delineating how elements of emerging MOUD service models can reduce stigma and increase behavior in pursuit of life goals. Specifically, we outline how new approaches to three key processes can counter structural, public, and self-stigma for this population: (1) community outreach with peer-to-peer influence, (2) clinical evaluation and induction of MOUD in acute care settings, and (3) transition to outpatient maintenance care and early recovery. Emerging service models that target these three processes can, in turn, foster patient empowerment and pursuit of life goals. There is great potential to increase the well-being of people who use opioids by reducing stigma against MOUD via these structural changes.

An examination of college students’ unwanted pursuit of ex-romantic partners: relations to parental warmth and difficulties in emotion regulation

ABSTRACT Unwanted pursuit behaviours (UPBs) are behaviours that are often intended to initiate a relationship or restore romantic relationships following a break-up. Research shows relatively high prevalence rates of UPBs in college students. In the current study, we tested a conceptual mediation model, where perceived parental warmth would be indirectly related to UPBs via emotional regulation difficulties. College students (n = 314) completed online measures of parental warmth, emotion regulation difficulties, and perpetration of UPBs. We found that perceived parental warmth was significantly negatively related to perpetration of UPBs, and only impulse control difficulties showed a significant indirect effect. Parental warmth was directly associated with UPBs even after accounting for emotion regulation difficulties, suggesting that other factors may also explain the relation. Findings encourage future research into other developmental correlates of UPBs in prevention and intervention efforts.

Obstacle avoidance in aerial pursuit

Pursuing prey through clutter is a complex and risky activity requiring integration of guidance subsystems for obstacle avoidance and target pursuit. The unobstructed pursuit trajectories of Harris' hawks Parabuteo unicinctus are well modeled by a mixed guidance law feeding back target deviation angle and line-of-sight rate. Here we ask how their pursuit behavior is modified in response to obstacles, using high-speed motion capture to reconstruct flight trajectories recorded during obstructed pursuit of maneuvering targets.We find that Harris' hawks use the same mixed guidance law during obstructed pursuit but appear to superpose a discrete bias command that resets their flight direction to aim at a clearance of approximately one wing length from an upcoming obstacle as they reach some threshold distance from it. Combining a feedback command in response to target motion with a feedforward command in response to upcoming obstacles provides an effective means of prioritizing obstacle avoidance while remaining locked-on to a target. We therefore anticipate that a similar mechanism may be used in terrestrial and aquatic pursuit. The same biased guidance law could also be used for obstacle avoidance in dronesdesigned to intercept other drones in clutter, or to navigate between fixed waypoints in urban environments.

The influence of Safety Perception according of college students majoring in physical education on Perception of risk and Safety Pursuit Behavior

The influence of Safety Perception according of college students majoring in physical education on Perception of risk and Safety Pursuit Behavior

Strategic predatory pursuit of the stealthy, highly manoeuvrable, slow flying bat Corynorhinus townsendii.

A predator's capacity to catch prey depends on its ability to navigate its environment in response to prey movements or escape behaviour. In predator-prey interactions that involve an active chase, pursuit behaviour can be studied as the collection of rules that dictate how a predator should steer to capture prey. It remains unclear how variable this behaviour is within and across species since most studies have detailed the pursuit behaviour of high-speed, open-area foragers. In this study, we analyse the pursuit behaviour in 44 successful captures by Corynorhinus townsendii, Townsend's big-eared bat (n = 4). This species forages close to vegetation using slow and highly manoeuvrable flight, which contrasts with the locomotor capabilities and feeding ecologies of other taxa studied to date. Our results indicate that this species relies on an initial stealthy approach, which is generally sufficient to capture prey (32 out of 44 trials). In cases where the initial approach is not sufficient to perform a capture attempt (12 out of 44 trials), C. townsendii continues its pursuit by reacting to prey movements in a manner best modelled with a combination of pure pursuit, or following prey directly, and proportional navigation, or moving to an interception point.

Visual versus visual-inertial guidance in hawks pursuing terrestrial targets.

The aerial interception behaviour of falcons is well modelled by a guidance law called proportional navigation, which commands steering at a rate proportional to the angular rate of the line-of-sight from predator to prey. Because the line-of-sight rate is defined in an inertial frame of reference, proportional navigation must be implemented using visual-inertial sensor fusion. By contrast, the aerial pursuit behaviour of hawks chasing terrestrial targets is better modelled by a mixed guidance law combining information on the line-of-sight rate with information on the deviation angle between the attacker's velocity and the line-of-sight. Here we ask whether this behaviour may be controlled using visual information alone. We use high-speed motion capture to record n = 228 flights from N = 4 Harris' hawks Parabuteo unicinctus, and show that proportional navigation and mixed guidance both model their trajectories well. The mixed guidance law also models the data closely when visual-inertial information on the line-of-sight rate is replaced by visual information on the motion of the target relative to its background. Although the visual-inertial form of the mixed guidance law provides the closest fit, all three guidance laws provide an adequate phenomenological model of the behavioural data, whilst making different predictions on the physiological pathways involved.

Anterior insula and dorsal anterior cingulate cortex as a hub of self-regulation: combining activation likelihood estimation meta-analysis and meta-analytic connectivity modeling analysis.

Self-regulation, which is an individual's ability to control their emotions and behaviors in pursuit of goals, is a complex cognitive function that relies on distributed brain networks. Here, we used activation likelihood estimation (ALE) to conduct two large-scale meta-analyses of brain imaging studies of emotional regulation and behavioral regulation. We used single analysis of ALE to identify brain activation regions associated with behavioral regulation and emotion regulation. The conjunction results of the contrast analysis of the two domains showed that the crucial brain regions of dorsal anterior cingulate cortex (dACC), bilateral anterior insula (AI), and right inferior parietal lobule (IPL) are nested within the brain areas of the two regulation domains at the spatial and functional level. In addition, we assessed the coactivation pattern of the four common regions using meta-analytic connectivity modeling (MACM). The coactivation brain patterns based on the dACC and bilateral AI overlapped with the two regulation brain maps in a high proportion. Furthermore, the functional characters of the identified common regions were reverse-inferenced using the BrainMap database. Collectively, these results indicate that the brain regions of dACC and bilateral AI, playing a crucial role as a hub to other brain regions and networks by effective connectivity in self-regulation, are spatially nested in the brain network of behavioral regulation and emotion regulation.

Are Benefits of Participation Higher Than Risks? An Exploration of Reactions to Participation in Research on Intimate Partner Stalking Among College Young Adults.

Ethical guidelines dictate that research studies should present more benefit than harm to participants, thus, it is important to study participants' reactions to participation, particularly in the context of potentially traumatic topics. While several studies have indicated that positive evaluations of research typically outweigh perceived harms among survivors of physical, sexual, or psychological intimate partner violence, few studies have assessed survivors of intimate partner stalking (IPS) or unwanted pursuit behaviors (UPBs). Among 602 undergraduates (78% women), the present study examined reactions to research participation in a study on IPS/UPBs. Results indicated that, among victims and non-victims of IPS, positive global evaluations and perceived benefits outweighed negative emotional reactions and perceived drawbacks to participation. While some participants (7.5%) reported emotional reactions to participation, most, on average, evaluated the study positively (94.4%), many reported benefits (45.5%), and just one (0.2%) reported drawbacks. Emotional reactions were positively correlated with both drawbacks and benefits of participation. Frequency of UPBs/IPS and IPV were positively correlated with emotional reactions to participation; however, when included in a model with psychological distress (i.e., post-traumatic stress disorder and depressive symptoms), symptom frequencies were more strongly related to reactions to research than victimization variables. In all, research on IPS/UPBs appears to be evaluated generally positively and can likely be undertaken safely when using safeguards to inform participants and debrief them following participation.

Driving risk prevention in usage-based insurance services based on interpretable machine learning and telematics data

Usage-based insurance (UBI) adjusts premiums based on an individual policyholder’s dynamic risk evaluation, incentivizing policyholders to maintain safe driving behavior in pursuit of a lower insurance premium. Although post-trip interventions can improve driving behavior significantly, most interventions do not provide risk mitigation strategies tailored to long-term driving behavior. This study proposes a novel approach for driving risk prevention in UBI services, providing risk analysis services and tailoring driving suggestions for policyholders. Advanced prediction models and model interpretation methods were adopted to assess and analyze personal driving risks, respectively. A multi-objective counterfactual model was developed to generate risk mitigation strategies for policyholders. The significance of driving behavior in risk mitigation and its actionability were assessed to provide realistic and actionable suggestions for policyholders. The case study, based on a real dataset from an insurance company in China, showed that the proposed approach can be directly embedded in the existing UBI service framework to provide personalized feedback and services to policyholders.

A Pluralist Approach to Joint Responsibility

A Pluralist Approach to Joint Responsibility

Attenuation of noise correlations in the transformation from the frontal eye field to movement.

Correlated activity between neurons can cause variability in behavior across trials, as trial-by-trial cofluctuations can propagate downstream through the motor system. The extent to which correlated activity affects behavior depends on the properties of the translation of the population activity into movement. A major hurdle in studying the effects of noise correlations on behavior is that in many cases this translation is unknown. Previous research has overcome this by using models that make strong assumptions about the coding of motor variables. We developed a novel method that estimates the contribution of correlations to behavior with minimal assumptions. Our method partitions noise correlations into correlations that are expressed in a specific behavior, termed behavior-related correlations, and correlations that are not. We applied this method to study the relationship between noise correlations in the frontal eye field (FEF) and pursuit eye movements. We defined a distance metric between the pursuit behavior on different trials. Based on this metric, we used a shuffling approach to estimate pursuit-related correlations. Although the correlations were partially linked to variability in the eye movements, even the most constrained shuffle strongly attenuated the correlations. Thus, only a small fraction of FEF correlations is expressed in behavior. We used simulations to validate our approach, show that it captures behavior-related correlations, and demonstrate its generalizability in different models. We show that the attenuation of correlated activity through the motor pathway could stem from the interplay between the structure of the correlations and the decoder of FEF activity.NEW & NOTEWORTHY The effect of noise correlations on neural computations has been studied extensively. However, the degree to which correlations affect downstream areas remains unknown. Here, we take advantage of precise measurement of eye movement behavior to estimate the degree to which correlated variability between neurons in the frontal eye field (FEF) affects subsequent behavior. To achieve this, we developed a novel shuffling-based method and verified it using different models of the FEF.

Hoverfly (Eristalis tenax) pursuit of artificial targets.

The ability to visualize small moving objects is vital for the survival of many animals, as these could represent predators or prey. For example, predatory insects, including dragonflies, robber flies and killer flies, perform elegant, high-speed pursuits of both biological and artificial targets. Many non-predatory insects, including male hoverflies and blowflies, also pursue targets during territorial or courtship interactions. To date, most hoverfly pursuits have been studied outdoors. To investigate hoverfly (Eristalis tenax) pursuits under more controlled settings, we constructed an indoor arena that was large enough to encourage naturalistic behavior. We presented artificial beads of different sizes, moving at different speeds, and filmed pursuits with two cameras, allowing subsequent 3D reconstruction of the hoverfly and bead position as a function of time. We show that male E. tenax hoverflies are unlikely to use strict heuristic rules based on angular size or speed to determine when to start pursuit, at least in our indoor setting. We found that hoverflies pursued faster beads when the trajectory involved flying downwards towards the bead. Furthermore, we show that target pursuit behavior can be broken down into two stages. In the first stage, the hoverfly attempts to rapidly decreases the distance to the target by intercepting it at high speed. During the second stage, the hoverfly's forward speed is correlated with the speed of the bead, so that the hoverfly remains close, but without catching it. This may be similar to dragonfly shadowing behavior, previously coined 'motion camouflage'.