Self-Organization, Selection and Emergence in the Theories of Evolution

Feltz, Bernard

doi:10.1007/1-4020-3917-4_20

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…Biology, Chemistry and Physics share the study of individual parts of different systems to explain their global behaviour. The manifestation of emergence [36][37][38][39] is a good example of such studies. In it, the microscopic characteristics enable the arising of unexpected macroscopical behaviour.…”

Section: Related Workmentioning

confidence: 99%

Estimating the Expected Time to Enter and Leave a Common Target Area in Robotic Swarms

Passos

Marcolino

2023

Preprint

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Coordination algorithms are required to minimise congestion when every robot in a robotic swarm has a common target area to visit. Some of these algorithms use artificial potential fields to enable path planning to become distributed and local. An efficiency measure for comparing them is the time to complete a task in relation to the number of individuals in the swarm. In order to compare distinct solutions as the swarm grows, experiments with different numbers of robots must be simulated to form a plot of the function of the task completion time versus the number of robots or other parameters. Nevertheless, plotting it for many robots through simulation is time-consuming. Additionally, the inference of a global swarm behaviour as the task completion time from the local individual robot motion controller based on potential fields and other dynamical variables is intractable and requires experimental analysis. Based on that, we present equations for estimating the expected task completion time of state-of-the-art algorithms, robots using only attractive and repulsive force fields and mixed teams for the common target area problem in robotic swarms with not only the number of robots as input but also environment- and algorithm-related global variables, such as the size of the common target area and the working area, average speed and average distance between the robots. This paper is a fundamental first step to start a discussion on how better approximations can be achieved and which mathematical theories about local-to-global analysis are better suited to this problem.

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Section: Related Workmentioning

confidence: 99%

Estimating the Expected Time to Enter and Leave a Common Target Area in Robotic Swarms

Passos

Marcolino

2023

Preprint

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“…One of the implications of the definition of complexity provided above is that the creation of systems through the interaction between individual involves a process called "self-organization" or "self-assembly." Although originating from physics (Glansdorff & Prigogine, 1971), the idea has found wide application, including in the social and life sciences, where it has been argued that through interaction, individual components create and maintain systemic structures that may reorganize in response to environmental pressure (Feltz et al, 2006).…”

Section: Complexitymentioning

confidence: 99%

Growing Points for a Synthesis Between the Sciences of Learning, School Reform, and Inequity: Insights From Complex Dynamical Systems Theory

Koopmans

2023

Review of Research in Education

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The growing differentiation of specialties in education creates the need for a common framework. This chapter discusses the basic premises of complex dynamical systems theory (CDST), its intellectual foundations, and its applicability to the field of education, with a particular focus on the areas of learning and development, school reform, and the persistence of inequity in society. The vocabulary of CDST is reviewed and applied to these problem areas to help deepen our understanding of the challenges facing policymakers and practitioners and provide growing points for the integration of these areas of knowledge into a coherent basis for further research and exploration. The differences between CDST and traditional research paradigms are also duly considered.

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“…A group of vessels, not necessarily part of a particular fleet, will be governed by specific rules during traffic and their interactions with nearby vessels and the environment. Some organized structures (patterns) thereby emerge spontaneously, much like the flocking and schooling of a swarm of birds or fish [11,12]. Unlike many studies on simulating collective dynamics using the bottom-up approach [13][14][15], we aim to do the opposite: recognizing group-level vessel patterns from real movement data to infer their collective behaviors.…”

Section: Introductionmentioning

confidence: 99%

Recognizing Instantaneous Group Patterns in Vessel Trajectory Data: A Snapshot Perspective

Zhang,

Zhou,

2023

JMSE

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Recognizing vessel navigation patterns plays a vital role in understanding maritime traffic behaviors, managing and planning vessel activities, spotting outliers, and predicting traffic. However, the growth in trajectory data and the complexity of maritime traffic in recent years presents formidable challenges to this endeavor. Existing approaches predominantly adopt a ‘trajectory perspective’, where the instantaneous behaviors of vessel groups (e.g., the homing of fishing vessels) that occurred at certain times are concealed in the massive trajectories. To bridge this gap and to reveal collective patterns and behaviors, we look at vessel patterns and their dynamics at only individual points in time (snapshots). In particular, we propose a recognition framework from the snapshot perspective, mixing ingredients from group dynamics, computational geometry, graph theory, and visual perception theory. This framework encompasses algorithms for detecting basic types of patterns (e.g., collinear, curvilinear, and flow) and strategies to combine the results. Case studies were carried out using vessel trajectory (AIS) data around the Suez Canal and other areas. We show that the proposed methodology outperformed DBSCAN and clustering by measuring local direction centrality (CDC) in recognizing fine-grained vessel groups that exhibit more cohesive behaviors. Our results find interesting collective behaviors such as convoy, turning, avoidance, mooring (in open water), and berthing (in the dock), and also reveal abnormal behaviors. Such results can be used to better monitor, manage, understand, and predict maritime traffic and/or conditions.

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Self-Organization, Selection and Emergence in the Theories of Evolution

Cited by 4 publications

References 14 publications

Estimating the Expected Time to Enter and Leave a Common Target Area in Robotic Swarms

Estimating the Expected Time to Enter and Leave a Common Target Area in Robotic Swarms

Growing Points for a Synthesis Between the Sciences of Learning, School Reform, and Inequity: Insights From Complex Dynamical Systems Theory

Recognizing Instantaneous Group Patterns in Vessel Trajectory Data: A Snapshot Perspective

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