Dynamic systems methods for models of developmental psychopathology

2003 ◽  
Vol 15 (3) ◽  
pp. 641-669 ◽  
Author(s):  
ISABELA GRANIC ◽  
TOM HOLLENSTEIN
Keyword(s):  
State Space ◽  
Dynamic Systems ◽  
Developmental Psychopathology ◽  
Open Systems ◽  
Change Processes ◽  
New Methods ◽  
Research Designs ◽  
State Space Grids ◽  
Systems Models ◽  
The One

A survey of dynamic systems (DS) methods appropriate for testing systems-based models in developmental psychopathology is provided. The rationale for developing new methods for the field is reviewed first. In line with other scholars, we highlight the fundamental incompatibility between developmentalists' organismic, open systems models and the mechanistic research methods with which these models are tested. Key DS principles are explained and their commensurability with developmental psychopathologists' core theoretical concerns are discussed. Next, a survey of research designs and methodological techniques currently being used and refined by developmental DS researchers is provided. The strengths and limitations of each approach are discussed throughout this review. Finally, we elaborate on one specific dynamic systems method, state space grids, which addresses many of the limitations of previous DS techniques and may prove most useful for the discipline. This approach was developed as a middle road between DS methods that are mathematically heavy on the one hand and purely descriptive on the other. Examples of developmental and clinical studies that have applied state space grids are reviewed and suggestions for future analyses are made. We conclude with some implications for the application of this new methodology for studying change processes in clinical research.

State space grids: Analyzing dynamics across development

2007 ◽  
Vol 31 (4) ◽  
pp. 384-396 ◽  
Author(s):  
Tom Hollenstein
Keyword(s):  
State Space ◽  
Longitudinal Studies ◽  
Real Time ◽  
Dynamic Systems ◽  
Developmental Change ◽  
Theoretical Models ◽  
The State ◽  
Event Sequences ◽  
The Past ◽  
State Space Grids

Developmentalists are generally interested in systems perspectives and this is reflected in the theoretical models of the past decade. However, the methodological tools to test these models are either nonexistent or difficult for many researchers to use. This article reviews the state space grid (SSG) method for analyzing synchronized event sequences based on dynamic systems (DS) principles. Following a review of these DS concepts and the basics of the SSG method, several studies are reviewed. Greater emphasis and detail are provided for three longitudinal studies that relate real-time socioemotional dynamics to processes of developmental change and stability. The concluding sections provide guidelines for researchers interested in using the SSG method and some suggestions for future SSG studies.

scholarly journals The Hubble hypothesis and the developmentalist's dilemma

1997 ◽  
Vol 9 (2) ◽  
pp. 193-229 ◽  
Author(s):  
JOHN E. RICHTERS
Keyword(s):  
Closed System ◽  
Developmental Psychopathology ◽  
Open Systems ◽  
Research Process ◽  
Explanatory Models ◽  
Indigenous Research ◽  
Research Strategies ◽  
Developmental Principles ◽  
The One ◽  
Analytic Models

Developmental psychopathology stands poised at the close of the 20th century on the horns of a major scientific dilemma. The essence of this dilemma lies in the contrast between its heuristically rich open system concepts on the one hand, and the closed system paradigm it adopted from mainstream psychology for investigating those models on the other. Many of the research methods, assessment strategies, and data analytic models of psychology's paradigm are predicated on closed system assumptions and explanatory models. Thus, they are fundamentally inadequate for studying humans, who are unparalleled among open systems in their wide ranging capacities for equifinal and multifinal functioning. Developmental psychopathology faces two challenges in successfully negotiating the developmentalist's dilemma. The first lies in recognizing how the current paradigm encourages research practices that are antithetical to developmental principles, yet continue to flourish. I argue that the developmentalist's dilemma is sustained by long standing, mutually enabling weaknesses in the paradigm's discovery methods and scientific standards. These interdependent weaknesses function like a distorted lens on the research process by variously sustaining the illusion of theoretical progress, obscuring the need for fundamental reforms, and both constraining and misguiding reform efforts. An understanding of how these influences arise and take their toll provides a foundation and rationale for engaging the second challenge. The essence of this challenge will be finding ways to resolve the developmentalist's dilemma outside the constraints of the existing paradigm by developing indigenous research strategies, methods, and standards with fidelity to the complexity of developmental phenomena.

Studying dynamic systems models in Simulink

2016 ◽  
Author(s):  
Galina Ivanovna Popova ◽  
◽  
Yuliya Nikolaevna Prilepskaya ◽  
Keyword(s):  
Dynamic Systems ◽  
Systems Models

scholarly journals Generalized Representation Learning Methods for Deep Reinforcement Learning

2020 ◽  
Author(s):  
Hanhua Zhu
Keyword(s):  
Reinforcement Learning ◽  
State Space ◽  
Representation Learning ◽  
Learning Methods ◽  
New Methods ◽  
Compact State

Deep reinforcement learning (DRL) increases the successful applications of reinforcement learning (RL) techniques but also brings challenges such as low sample efficiency. In this work, I propose generalized representation learning methods to obtain compact state space suitable for RL from a raw observation state. I expect my new methods will increase sample efficiency of RL by understandable representations of state and therefore improve the performance of RL.

INFORMATION AND TELECOMMUNICATION NETWORK SECURITY MANAGEMENT METHODOLOGY

2021 ◽  
Author(s):  
М.А. КАРПОВ ◽  
М.В. МИТРОФАНОВ ◽  
О.С. ЛАУТА ◽  
Д.А. ПАЛЬЦИН
Keyword(s):  
State Space ◽  
Dynamic Systems ◽  
Telecommunication Network ◽  
The State ◽  
Complex Dynamic ◽  
Computing Power ◽  
Complex Dynamic Systems ◽  
Situational Management ◽  
The Cost ◽  
Network Security Management

Исследуются вопросы ситуативного управления сложными динамическими системами. Анализируются релевантные работы в области ситуативного управления системами защиты. Приводятся результаты разработки алгоритма эффектив -ного управления, позволяющего уменьшать пространство состояний управляемого объекта. Показано, что представленная методика позволяет спрогнозировать количество итераций управления в зависимости от сегмента пространства состояний и выбранного количества переходов. Данный подход позволяет воздействовать на сложные динамические системы в реальном времени, причем затраты на вычислительные мощности системы управления и ее подсистем сокращаются. The issues of situational management of complex dynamic systems are investigated. Relevant works in the field of situational management of protection systems are analyzed. The article presents the results of the development of an efficient control algorithm that allows reducing the state space of the controlled object. The presented technique makes it possible to predict the number of control iterations depending on the segment of the state space and the selected number of transitions. This approach allows you to act on complex dynamic systems in real time, while the cost of the computing power of the control system and its subsystems is reduced. Keywords: INFORMATION AND TELECOMMUNICATION NETWORK, SCRIPT FORECAST, MANAGEMENT SYSTEM, SITUATIONAL MANAGEMENT, ITCN SECURITY SYSTEM

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