ANTIFRAGILE 2020 - The 7th International Workshop on Computational Antifragility and Antifragile Engineering

Resilience is one of those "general systems attributes" that appear to play a central role in several disciplines--including ecology, business, psychology, industrial safety, microeconomics, computer networks, security, management science, cybernetics, control theory, crisis and disaster management. Despite being such an important systemic ingredient, no consensual definition of resilience has been proposed. Perhaps resilience could be better captured by considering the Aristotelian concept of entelechy: a resilient system is an entelechy, namely one that strives to preserve its characteristics; or with the words of Aristotle, it "is-AT-work to stay-the-same", meaning that an antifragile system autonomosly adapts its function, structure, and identity, in order to systematically improve its system-environment fit. An antifragile system is thus one that may sacrifice some of its peculiar characteristics so long as it matches better with the conditions timely expressed by its deployment environment. It is a system able to take autonomic decisions as to its own adaptation and evolution.
Engineering a resilient system thus means designing a system whose major goal is to preserve its identity, and does so by adapting its function and structure so as to compensate for faults, failures, and attacks. In the context of computer systems, system identity is the set of functional and non-functional properties that are to characterize the system given the specifications of that system.
If we define resilience as above, it is easier to understand what is Antifragility, the concept recently highlighted by Professor Nassim Nicholas Taleb in his book. Antifragility is the property of a system that "is-AT-work to get better",
This means that an antifragile system would autonomosly adapt its function, structure, and identity, in order to systematically improve its system-environment fit. An antifragile system is thus one that may sacrifice some of its peculiar characteristics (at least, peculiar with reference to its specification!) so long as it matches better with the conditions timely expressed by its deployment environment. It is a system able to take autonomic decisions as to its own adaptation and evolution.
As explained, e.g., in this article by Dr. Kennie H. Jones of NASA, the engineering of antifragile computer-based systems is a challenge that, once met, would allow systems and ambients to self-evolve and self-improve by learning from accidents and mistakes in a way not dissimilar to that of human beings. Learning how to design and craft antifragile systems is an extraordinary challenge whose tackling is likely to reverberate on many a computer engineering field. New methods, programming languages, even custom platforms will have to be designed. The expected returns are extraordinary as well: antifragile computer engineering promises to enable realizing truly autonomic systems and ambients able to meta-adapt to changing circumstances; to self-adjust to dynamically changing environments and ambients; to self-organize so as to track dynamically and proactively optimal strategies to sustain scalability, high-performance, and energy efficiency; to personalize their aspects and behaviors after each and every user. And to learn how to get better while doing it.
Learning how to design and craft antifragile systems is an extraordinary challenge whose tackling is likely to reverberate on many a computer engineering field. New methods, programming languages, even custom platforms will have to be designed. The expected returns are extraordinary as well: antifragile computer engineering promises to enable realizing truly autonomic systems and ambients able to meta-adapt to changing circumstances; to self-adjust to dynamically changing environments and ambients; to self-organize so as to track dynamically and proactively optimal strategies to sustain scalability, high-performance, and energy efficiency; to personalize their aspects and behaviors after each and every user. And to learn how to get better while doing it. The last six Editions of our workshop were enriched by the participation of Professor Taleb and Dr. Kennie H. Jones who kindly provided their keynote speeches. Today we aim to further enhance the awareness of the challenges of antifragile engineering and extend the discussion on how computer and software engineering may address them, also considering additional domains where antifragile behaviors would be very desirable. In particular, we shall consider two new domains to this seventh Edition of ANTIFRAGILE:
A first domain is antifragile transition onto sustainable development: Thus far, societal transitions have been spontaneous collective behaviors that did not result in any sustainable relationship with our environments. Interaction between the human societies and the global eco-system they inhabit interaction has resulted in phenomena that in the long run could endanger our species and the whole planet. Is an antifragile, human-induced transition onto sustainable development possible? How to design and steer such a transition so that our societies learn to systematically improve the human-environment fit?
A second domain is antifragile drone control: The focus here is air traffic management and how the advent of drones is impacting on all aspects of the air transportation industry. Self-learning, self-safe drones could represent a key ingredient to prevent disruptions and accidents.
As a design aspect cross-cutting through all system and communication layers, antifragile engineering calls for multi-disciplinary visions and approaches able to bridge the gaps between “distant” research communities so as to:
propose novel solutions to design, develop, and evaluate antifragile systems and ambients
devise computational models and paradigms for antifragile engineering
provide analytical and simulation models and tools to measure a system's ability to withstand faults, adjust to new environments, and enhance their identity and resilience in the process
foster the exchange of ideas and promote discussions able to steer future research and development efforts in the area of computational antifragility
The main topics of the workshop include, but are not limited to:
Antifragile Societal Transitions
Antifragile Drone Systems
Antifragile Social Systems
Antifragile Cities
Antifragile Communities
Antifragile Services
Antifragile Learning (Evolving Learning Machines)
Machine learning as a foundation to antifragile behaviors: Reinforcement learning, deep learning, and so on
Antifragile games
Antifragile cars
Internet-of-(Antifragile?)-Things
Conceptual frameworks for antifragile systems, ambients, and behaviours
Dependability, resilience, and antifragile requirements and open issues
Design principles, models, and techniques for realizing antifragile systems and behaviours
Frameworks and techniques enabling resilient and antifragile applications
Discussion and analysis if antifragile applications
Antifragile human-machine interaction
End-to-end approaches towards antifragile services
Autonomic antifragile behaviours
Middleware architectures and mechanisms for resilience and antifragility
Theoretical foundation of resilient and antifragile behaviours
Formal methods for resilience and antifragility
Programming language support for resilience and antifragility
Machine learning as a foundation of resilient and antifragile architectures
Antifragility and resiliency against malicious attacks
Modeling of antifragile systems (e.g., through Petri Nets)
Antifragility and the Cloud
Resilience and antifragility in human-computer interaction
Identity drifting in evolving systems (e.g., security aspects)
Specification and verification of resilient and antifragile systems
Programming language support for antifragility
Models of concurrent behaviors of "parts" leading to antifragile behaviors of the "whole"
Safety and security issues with reference to systems able to self-evolve their identity
Ethics issues related to antifragility