Resilience learning through self adaptation in digital twins of human-cyber-physical systems

• Human-Cyber-Physical-Systems (HPCS), such as critical infrastructures in modern society, are subject to several systemic threats due to their complex interconnections and interdependencies. Management of systemic threats requires a paradigm shift from static risk assessment to holistic resilience modeling and evaluation using intelligent, data-driven and run-time approaches. In fact, the complexity and criticality of HCPS requires timely decisions considering many parameters and implications, which in turn require the adoption of advanced monitoring frameworks and evaluation tools. In order to tackle such challenge, we introduce those new paradigms in a framework named RESILTRON, envisioning Digital Twins (DT) to support decision making and improve resilience in HCPS under systemic stress. In order to represent possibly complex and heterogeneous HCPS, together with their environment and stressors, we leverage on multi-simulation approaches, combining multiple formalisms, data-driven approaches and Artificial Intelligence (AI) modelling paradigms, through a structured, modular and compositional framework. DT are used to provide an adaptive abstract representation of the system in terms of multi-layered spatially-embedded dynamic networks, and to apply self-adaptation to time-warped What-If analyses, in order to find the best sequence of decisions to ensure resilience under uncertainty and continuous HPCS evolution.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Produktionsteknik, arbetsvetenskap och ergonomi (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Production Engineering, Human Work Science and Ergonomics (hsv//eng)

Nyckelord

artificial intelligence

Complex networks

Cyber Physical System

Decision making

E-learning

Embedded systems

Information management

Risk assessment

Security of data

Uncertainty analysis

Abstract representation

Advanced monitoring

Data-driven approach

Evaluation tool

Resilience model

Simulation approach

Static risk assessments

What-if Analysis

Digital twin

Computer Science

Datavetenskap

Publikations- och innehållstyp

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