Pursuit Time Research Articles

Some Results on Pursuit Games for an Infinite System of Ternary Differential Equations

This paper aims to study a one-pursuer, one evader pursuit differential game for a higher level of infinite system that is an infinite system of first order ternary differential equations, and prove completion of pursuit in the game. Both integral constraints and geometric constraints are subjected on the players' control functions, thus two separate cases of pursuit games are examined. In the game, the pursuer wants to take the state of the system into the origin of l2 space at some finite time interval, whereas evader avoids this from happening. For every case, we solve the control problem by establishing the admissible control function. In order to achieve the pursuer's objective, we then construct an admissible strategy for the pursuer and develop an equation for the guaranteed pursuit time of the game.

THE POETICS OF UTOPIA IN THE WORKS OF A. V. CHAYANOV

The futurological model presented in “My brother Alexei’s Journey to the Land of Peasant Utopia” by A. V. Chayanov (under the name of Iv. Kremnev) is focused on preserving and reviving the traditions of the times past, which are harmoniously integrated into a new way of life. The utopian worldview is very eclectic: along with manual agricultural labor, there are the latest inventions: meteorophores and aircraft, atmospheric precipitation is controlled. Art as a philosophical imperative defines all aspects of society. The leaders of the state, rely on the achievements of eugenics, striving to maximize the realization of each person’s talent, education is based on the principles of harmonious personal development: utopia’s residents not only master a specialty, but must know the history of art, play sports, which should also serve to reveal their abilities. The ideal is formed by both the ancient culture and manor pastime, where a person works in close contact with nature, spending leisure time in literary or musical pursuits. Knowledge of history and art is considered fundamental here: even cooking and entertainment are focused on preserving the memory of the past. Many of the ideas on which utopia is based are Chayanov’s ideas about the proper structure of education, its cultural and art history components, pedagogical and methodological principles, and the formation of a versatile and multifaceted scientist. But in a way, it is also an answer to the disputes of the late 19th — early 20th centuries about the role of man as a theurgist, the limits of his capabilities and power.

Swarm-to-swarm orbital pursuit method under delta-v maneuver for space pursuit-evasion

This paper investigates the orbital pursuit strategy for spacecraft swarms, where both pursuers and evaders possess limited delta-v maneuvering capabilities. Given that swarms can consist of numerous members, ranging from dozens to thousands, the swarm-to-swarm problem has significant coupling effects that cannot be solved by merely superimposing one-to-one or few-to-few problems. Otherwise, one would cause a dimension explosion in decision-making space. To avoid this issue, the swarm orbital pursuit problem is divided into two coupled problems: swarm target allocation and orbital maneuver. First, considering the relative orbit state between pursuers and evaders and estimated orbital maneuver costs of pursuit, the swarm target allocation problem is formulated into three coupled sub-problems, i.e., target allocation order, target allocation for sub-swarms, and target allocation for individuals. These sub-problems are solved by the presented double-layer contract net protocol algorithm to maximize task completion efficiency. Then, the orbital maneuver problem is decomposed into two coupled problems to maximize pursuit benefits, i.e., long-range rendezvous, and close-distance game maneuvers. For the long-range rendezvous, the optimal Lambert algorithm is developed to efficiently obtain the discrete optimal pursuit time and corresponding orbital transfer maneuver. To address close-distance games more proficiently, a hybrid orbital maneuver algorithm, combining the proximal policy optimization and the Lambert algorithm is proposed. Finally, comparison simulations verified the effectiveness and superiority of the proposed method.

The Relationship between Participation in Extracurricular Arts and Sports Activities and Adolescents' Social and Emotional Skills: An Empirical Analysis Based on the OECD Social and Emotional Skills Survey.

In light of the 'double reduction' policy, which affords adolescents increased time for extracurricular pursuits, the strategic organization of these activities' form and content is imperative. Prior research has established a robust correlation between adolescent participation in extracurricular arts and sports and the enhancement in their social and emotional skills. Nevertheless, the relationship between extracurricular arts and sports activities and the various dimensions of social and emotional skills, as well as the connection between participation in different types of these activities and the enhancement in social and emotional skills, requires further investigation. Utilizing the Theory of Multiple Intelligence and data from the OECD-SSES2019 Suzhou (China) student survey, this study employs Ordinary Least Squares (OLS) and coarsened exact matching (CEM) methodologies to address these gaps. In China, participation in extracurricular arts and sports activities is significantly positively associated with various dimensions of social and emotional skills, with a synergistic effect observed between these activities in enhancing these skills. Additionally, this study finds age-related heterogeneity in the relationship between participation in extracurricular arts and sports activities and the improvement in social and emotional skills.

L-CATCH GUARANTEED PURSUIT TIME

We consider a simple motion differential game of one pursuer and one evader. The dynamic equation of the pursuer and evader is describe by first order and second order differential equation respectively. Control functions of the players are subject to integral constraints. We show that pursuit is completed in L-catch sense, that is for some distance L , the difference in positions of the pursuit and evader x(t) and y(t) respectively is smaller than L that is || y(t) - x(t) ||< L at some time t . We construct a formula for guaranteed pursuit time and prove that pursuit is possible at that time.

Floor Cleaning Robot using Android App

The contemporary household landscape is witnessing a paradigm shift towards enhanced intelligence and automation. The integration of home automation systems not only provides increased convenience but also affords individuals more time for other pursuits. This project endeavors to conceptualize and actualize a Vacuum Robot that operates autonomously and manually through a designated mobile application. The Vacuum Cleaner Robot, utilizing components such as Arduino Mega, Arduino Shield, LDR Sensor, Real-Time Clock, Motor Shield L293D, Ultrasonic Sensor, and IR Sensor, aims to streamline the cleaning process, replacing manual vacuuming with an efficient automated solution. The primary objective of this initiative is to successfully design and implement a prototype Vacuum Robot that adheres to user-friendly criteria outlined in the aforementioned context.

Algorithmic Decision-Making, Agency Costs, and Institution-Based Trust

Algorithm Decision Making (ADM) systems designed to augment or automate human decision-making have the potential to produce better decisions while also freeing up human time and attention for other pursuits. For this potential to be realised, however, algorithmic decisions must be sufficiently aligned with human goals and interests. We take a Principal-Agent (P-A) approach to the questions of ADM alignment and trust. In a broad sense, ADM is beneficial if and only if human principals can trust algorithmic agents to act faithfully on their behalf. This mirrors the challenge of facilitating P-A relationships among humans, but the peculiar nature of human-machine interaction also raises unique issues. The problem of asymmetric information is omnipresent but takes a different form in the context of ADM. Although the decision-making machinery of an algorithmic agent can in principle be laid bare for all to see, the sheer complexity of ADM systems based on deep learning models prevents straightforward monitoring. We draw on literature from economics and political science to argue that the problem of trust in ADM systems should be addressed at the level of institutions. Although the dyadic relationship between human principals and algorithmic agents is our ultimate concern, cooperation at this level must rest against an institutional environment which allows humans to effectively evaluate and choose among algorithmic alternatives.

GUARANTEED PURSUIT TIME OF A LINEAR DIFFERENTIAL GAME WITH GENERALIZED GEOMETRIC CONSTRAINTS ON PLAYERS CONTROL FUNCTIONS

In this study, simple motion differential game of one pursuer and oneevader is considered in Rn. Control functions of the players are subject tomore generalized geometric constraints. Pursuit is said to be completedat a finite time Γ whenever the distance between both players at time Γis zero.We obtain an estimate for the guaranteed pursuit time Γ and constructpursuer’s strategy that ensure completion of pursuit at the time Γ.

Leaders' Perspectives on Resources for Academic Success: Defining Clinical Effort, Academic Time, and Faculty Support.

For academic promotion, clinical faculty are expected to excel in clinical care, teaching, and scholarship. Ensuring adequate protected time and resources to engage in scholarly work in the face of competing clinical responsibilities is critical. The authors examined academic leaders' perspectives across affiliate hospitals of a large medical school regarding the definition of clinical full-time effort and academic time, best practices to enable academic success, and barriers to faculty advancement. Open-ended, semistructured, individual interviews were conducted with a purposive sample of clinical department and division heads. Interview data were examined to illuminate the range and commonalities in practices and to identify successful approaches. Interviews were conducted with 17 academic leaders across 6 affiliate hospitals. There was considerable variability in clinical full-time effort definition. "Academic time," more accurately characterized as "nonclinical time," was typically 1 day a week for nonshift specialties and mostly used for administrative work or completing clinical documentation. Certain departments were more explicit in designating and protecting time for academic pursuits; some had invested resources in intensive programs for academic advancement with built-in expectations for accountability. The impact of documentation burden was considerable in certain departments. Marked variability exists in time allocations for clinical and academic work, as well as in resources for academic success. This supports the potential value of establishing standards for defining and protecting academic time, motivating clinical faculty to engage in academic work, and building accountability expectations. Sharing best practices and setting standards may enhance academic advancement. Strategies to reduce documentation burden may enhance wellness.

A distributed multi-vehicle pursuit scheme: generative multi-adversarial reinforcement learning

Multi-vehicle pursuit (MVP) is one of the most challenging problems for intelligent traffic management systems due to multi-source heterogeneous data and its mission nature. While many reinforcement learning (RL) algorithms have shown promising abilities for MVP in structured grid-pattern roads, their lack of dynamic and effective traffic awareness limits pursuing efficiency. The sparse reward of pursuing tasks still hinders the optimization of these RL algorithms. Therefore, this paper proposes a distributed generative multi-adversarial RL for MVP (DGMARL-MVP) in urban traffic scenes. In DGMARL-MVP, a generative multi-adversarial network is designed to improve the Bellman equation by generating the potential dense reward, thereby properly guiding strategy optimization of distributed multi-agent RL. Moreover, a graph neural network-based intersecting cognition is proposed to extract integrated features of traffic situations and relationships among agents from multi-source heterogeneous data. These integrated and comprehensive traffic features are used to assist RL decision-making and improve pursuing efficiency. Extensive experimental results show that the DGMARL-MVP can reduce the pursuit time by 5.47% compared with proximal policy optimization and improve the pursuing average success rate up to 85.67%. Codes are open-sourced in Github.

Organizations Should Maintain Employee’s Work-Life Balance

The scope of the current study is to determine the challenges of employees in between work-life and personal life balance. Organizations should prioritize and maintain employees’ work-life balance. Work-life balance refers to the equilibrium between an employee's work responsibilities and their personal life, including family, hobbies, and personal well-being. When employees have a healthy work-life balance, they experience less stress and improve their working skills to achieve the targets, and this well-being leads to improved mental and physical health as well as work productivity. This descriptive research approach surveyed by 67 responses as simple random technique, provides a significant result toward organizations that they should maintain employee’s work-life balance. The research finds that organizations that prioritize work-life balance are more likely to attract and retain top talent. By the managing time, regular assessment and adjustment in work-life balance initiatives, organizations can enhance their employer brand and improve employee retention rates. Work-life balance allows employees to have time for personal pursuits and interests outside of work which can contribute to their creativity and innovation. When employees have a healthy work-life balance, they are more likely to have positive relationships with their colleagues and supervisors. Improved relationships can lead to better teamwork, collaboration, and a more positive work environment.

Two Hierarchical Guidance Laws of Pursuer in Orbital Pursuit–Evasion–Defense Game

In this study, differential game theory was applied to propose two guidance laws of a pursuer in an orbit pursuit–evasion–defense game. One was a conservative guidance law of maneuvering to absolute safety before pursuing the evader, and the other was a radical guidance law of playing with the defender only when necessary. Both guidance laws enable the pursuer to avoid the defender while pursuing the evader, but the radical guidance law reduces the pursuit time by moving the pursuer closer to the defender. The pursuer, defender, and evader are all spacecraft carrying three-axis thrusters that can provide independent thrust in three directions. The proximity dynamics processes of the participants were described by the Clohessy–Wiltshire equations. A method for solving the time-to-go analytically was proposed by simplifying the dynamics model to meet real-time requirements. The effectiveness of the two guidance laws was verified by numerical simulations, and the differences between the two laws were analyzed.

Aerial culling invasive alien deer with shotguns improves efficiency and welfare outcomes

Invasive alien deer (known in Australia as ‘feral deer’; hereafter, ‘alien deer’) are some of Australia’s worst emerging pest species. Recently, the Government of South Australia launched a four-year program to reduce the populations of alien fallow deer (Dama dama). The program will focus on coordinating landscape-scale aerial culls and seeks to deliver the most efficient and humane approach to aerial culling. We sourced data from a recent program trialling a new approach to aerial culling that incorporated advanced thermal technology and a second shooter with a shotgun to target fallow deer. We reviewed available video and audio records of 104 deer culled in the program to assess efficiency and welfare outcomes. We collected information on the number of shotgun and rifle rounds fired per animal, time between first shot with a shotgun and apparent death, and pursuit time. We completed field dissections of 20 individuals targeted in the program to assess the lethality of wounds inflicted with shotgun pellets. We also compared program costs and efficiency against published and unpublished data from ten other aerial-culling programs for alien deer in South Australia since 2009. A total of 383 shotgun rounds and 10 rifle rounds were used on 104 fallow deer in the focal program. We documented strong improvements to animal welfare for alien deer targeted with shotguns. The mean (± standard error) time between first shot and apparent death with a shotgun was 11.1 ± 0.7 seconds; mean pursuit time between detection and apparent death was 49.5 ± 3.4 seconds. Pursuit time increased with subsequent deer controlled within a group; the maximum pursuit time for any individual was 159.0 seconds. All autopsied animals had received lethal wounds from shotgun pellets, with 100% receiving lung-penetrating damage and 70% also receiving heart-penetrating damage. While a program that uses a shotgun and rifle combined with a second shooter and thermographer can cost more to mobilise, the outcomes measured in cost deer-1 made it the most cost-effective approach of any program we assessed. Control options that deliver improved animal welfare outcomes and increase efficiency are desirable for managing expanding populations of alien deer in South Australia and elsewhere.

Cooperative strategy for pursuit-evasion problem in the presence of static and dynamic obstacles

In complex and dynamic marine environments with multiple obstacles, efficient and flexible pursuit is a challenging task. This paper proposes a self-organizing cooperative pursuit strategy. First, the Apollonius circle is introduced as the final formation of the encirclement pattern, and the trajectory of the target is predicted on the basis of the least-squares method. To improve the efficiency of collision avoidance against static irregular obstacles and obtain a more reasonable collision avoidance path, we design a discretization method to describe the boundary of obstacles and combine it with the artificial potential field (APF) method. Furthermore, dynamic obstacle avoidance is considered to extend the applicability of the algorithm to a variety of obstacle environments. Compared with the common greedy algorithm, the simulation results show that in the obstacle free and static obstacle environment, the self-organizing cooperative pursuit algorithm can shorten the pursuit time and improve the movement consistency of the USVs swarm, and the obstacle avoidance route is smoother. In complex environments containing static obstacles and dynamic ships, the self-organizing cooperative pursuit algorithm can also pursuit escape targets effectively.

Optimal Pursuit Game of Two Pursuers and One Evader with the Grönwall-Type Constraints on Controls

We studied a simple motion differential game of two pursuers and one evader in R2. The control functions of players are subjected to the Grönwall-type constraints. If the state of the evader coincides with the state of a pursuer, then the game is considered complete. The pursuers attempt to complete the game as earlier as possible. The evader attempts to avoid being captured or delays the capture time. We found an equation for the optimal pursuit time and construct the optimal strategies of players.

Evaluating aerial net gunning and chemical immobilisation for capture of invasive sambar deer (Rusa unicolor) and red deer (Cervus elaphus) in alpine Australia

Context Deer species are expanding in distribution and abundance in Australia. There is increasing focus on the ecology of these species, but effective deer capture methods are needed for telemetry studies. Aims The aims of this study were to develop, assess and refine a helicopter-based capture technique for wild sambar deer (Rusa unicolor) and red deer (Cervus elaphus), based on trials in south-eastern Australia. Methods We captured and collared 14 sambar deer and five red deer in two operations in Kosciuszko National Park in 2021, using a combination of aerial net gunning and chemical immobilisation delivered via hand injection. Captured animals were fitted with GPS collars to track their movements and activity post-capture. Physiological measurements were recorded as a means of assessing responses to capture and to optimise animal welfare outcomes. Key results Twenty-two deer were pursued and captured, with a total mortality rate of 14% (n = 3). The frequency of mortalities decreased from the first operation (17%) to the second operation (10%), largely attributed to allowable helicopter pursuit times being reduced. Post-release movement data indicated that delayed mortality due to capture did not occur. Activity of collared deer was lowest immediately following collaring, suggesting the procedure caused short-term decreases in deer activity. Conclusions Aerial capture of wild sambar deer and red deer poses animal welfare risks, but these can be minimised through the refinement in net gunning and pharmacological procedures to minimise animal stress. Implications This study describes an effective method for the safe capture of sambar deer and red deer, which will assist future wildlife researchers to further refine helicopter-based capture protocols and to collect spatial ecology and survival information about these species.

Differential Game for an Infinite System of Two-Block Differential Equations

We present a pursuit differential game for an infinite system of two-block differential equations in Hilbert space l2. The pursuer and evader control functions are subject to integral constraints. The differential game is said to be completed if the state of the system falls into the origin of l2 at some finite time. The purpose of the pursuer is to bring the state of the controlled system to the origin of the space l2, whereas the evader’s aim is to prevent this. For the optimal pursuit time, we obtain an equation and construct the optimal strategies for the players.

Habitat Complexity Alters Predator-Prey Interactions in a Shallow Water Ecosystem

Habitat complexity can profoundly influence interactions between predators and their prey due to changes to foraging efficiencies. In aquatic systems, habitat alterations can alter pursuit times and swimming behaviours of predator–prey participants, which in turn could mediate the strength of their interactions and, thus, population dynamics. The lower reaches of estuarine ecosystems are typically characterised by extensive beds of submerged macrophytes that might influence the trophic dynamics between pelagic predators and their prey. Here, we investigate the influence of increasing habitat complexity on the consumption of the calanoid copepod, Paracartia longipatella, by adult male and female mysid, Mesopodopsis wooldridgei, by means of a comparative functional response approach. Using structures that resembled aquatic vegetation, we quantified and compared feeding rates, attack rates, and handling times across the habitat gradient, and we questioned whether responses to habitat complexity are different between sexes. Feeding rates related significantly negatively to increasing habitat complexity for both males and females, with Type II functional responses consistently displayed. Functional response differed significantly across habitat complexities, with feeding rates at low and intermediate prey densities significantly greater in the absence of habitat compared to more complex structures for both predator sexes. Results of the current study demonstrate that increased habitat complexity mediates outcomes of interactions between M. wooldridgei and the calanoid copepod, P. longipatella across predator sexes, and possibly for other predators and prey in shallow waters. Owing to spatiotemporal differences in habitat structure within shallow waters, the strength of interactions in this predator–prey system likely differs in areas where they co-exist.

T3OMVP: A Transformer-Based Time and Team Reinforcement Learning Scheme for Observation-Constrained Multi-Vehicle Pursuit in Urban Area

Smart Internet of Vehicles (IoVs) combined with Artificial Intelligence (AI) will contribute to vehicle decision-making in the Intelligent Transportation System (ITS). Multi-vehicle pursuit (MVP) games, a multi-vehicle cooperative ability to capture mobile targets, are gradually becoming a hot research topic. Although there are some achievements in the field of MVP in the open space environment, the urban area brings complicated road structures and restricted moving spaces as challenges to the resolution of MVP games. We define an observation-constrained MVP (OMVP) problem in this paper and propose a transformer-based time and team reinforcement learning scheme (T3OMVP) to address the problem. First, a new multi-vehicle pursuit model is constructed based on Decentralized Partially Observed Markov Decision Processes (Dec-POMDPs) to instantiate this problem. Second, the QMIX is redefined to deal with the OMVP problem by leveraging the transformer-based observation sequence and combining the vehicle’s observations to reduce the influence of constrained observations. Third, a simulated urban environment is built to verify the proposed scheme. Extensive experimental results demonstrate that the proposed T3OMVP scheme achieves improvements relative to the state-of-the-art QMIX approaches by 9.66~106.25%, from simple to difficult scenarios.

Real-time acoustic modeling in the 2021 New England Shelf Break Acoustics experiment and beyond

Real-time acoustic modeling in a shipboard context emphasizes the element of computation time in pursuit of in situ comparison between observed ocean data and model output. The importance of computation time highlights two competing factors in efforts to produce real-time acoustic predictions: the quantity of models to run and model accuracy. During the 2021 New England Shelf Break Acoustics (NESBA) experiment, a four-dimensional (4D) model of acoustic signals in the experiment network comprised of multiple stationary sound sources and receivers was produced using shipboard high-performance computing (HPC) resources. This effort involved hundreds of acoustic model runs across four separate source and receiver pairings and allowed for in-situ model adjustments, ultimately producing favorable comparisons between data and models in a matter of days. This presentation will examine the HPC approaches taken during the NESBA science cruise and address the planned improvements to the system for future scientific field experiments. [This work is supported by the Office of Naval Research.]