COMPUTATION IS A TECHNOLOGY TO THINK WITH. It is an instrument for epistemological discovery. It changes not only what we know but how we know.
Computation was discovered as much as it was invented. It is part of how the universe works, including, as Blaise Agüera y Arcas gracefully shows, what intelligence is.
Among the many rich takeaways that await you as you read What is Intelligence? is that much of what is traditionally categorized as “life,” “intelligence,” and “technology” is combining in new ways (think synthetic biology, artificial life, and AI). So too are the definitions of these terms, in ways that would have been unthinkable only a few years ago.
Are these three words—life, intelligence, technology—actually different names for the effects of a more general process? Just as life is a factory for making more life, and technology is a factory for making more technology, now life makes technologies that make new life that makes new technologies. Ultimately, it may be the same factory, and at its heart is computation.
That such a claim could be made at all is due in no small part to the creative and curious use of our computational tools—or what we might more precisely call artificial computation. With these we discover that the otherwise imperceivable building blocks of our reality and of our own flesh are themselves computational. Computation discovers itself through us.

Read the full book at: whatisintelligence.antikythera.org

Cristian Axenie , Roman Bauer , Oliver López Corona , Jeffrey West

As coined in the book of Nassim Taleb, antifragility is a property of a system to gain from uncertainty, randomness, and volatility, opposite to what fragility would incur. An antifragile system’s response to external perturbations is beyond robust, such that small stressors can strengthen the future response of the system by adding a strong anticipation component. Such principles are already well suited for describing behaviors in natural systems but also in approaching therapy designs and eco-system modelling and eco-system analysis.

The purpose of this book is to build a foundational knowledge base by applying antifragile system design, analysis, and development in natural systems, including biomedicine, neuroscience, and ecology as main fields. We are interested in formalizing principles and an apparatus that turns the basic concept of antifragility into a tool for designing and building closed-loop systems that behave beyond robust in the face of uncertainty when characterizing and intervening in biomedical and ecological (eco)systems.

The book introduces the framework of applied antifragility and possible paths to build systems that gain from uncertainty. We draw from the body of literature on natural systems (e.g. cancer therapy, antibiotics, neuroscience, and agricultural pest management) in an attempt to unify the scales of antifragility in one framework. The work of the Applied Antifragility Group in oncology, neuroscience, and ecology led by the authors provides a good overview on the current research status.

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Cristian Axenie , Meisam Akbarzadeh , Michail A. Makridis , Matteo Saveriano , Alexandru Stancu

The book purpose is to build a foundational knowledge base by applying antifragile system design, analysis, and development in technical systems, with a focus on traffic engineering, robotics, and control engineering. The authors are interested in formalizing principles and an apparatus that turns the basic concept of antifragility into a tool for designing and building closed-loop technical systems that behave beyond robust in the face of uncertainty.

As coined in the book of Nassim Taleb, antifragility is a property of a system to gain from uncertainty, randomness, and volatility, opposite to what fragility would incur. An antifragile system’s response to external perturbations is beyond robust, such that small stressors can strengthen the future response of the system by adding a strong anticipation component. The work of the Applied Antifragility Group in traffic control and robotics, led by the authors, provides a good overview on the current research status.

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Interdisciplinary systems thinking is complementary but does not replace conventional disciplinary analytical thinking. The book is valuable for researchers, their advisors, and other thinkers interested in deep knowledge of science. Interdisciplinary systems thinking is valuable for three reasons: The goal of all science is a unified view of the world; we cannot solve the significant problems of our time without interdisciplinary collaboration; and general theories of systems and system archetypes support the solution to those problems. System archetypes are generic system models that have stood the test of time. As specialists within a discipline, we must be able to communicate between disciplines.
Interdisciplinary generalists can offer us reliable visions and relevant research problems. The goal of interdisciplinary research is to find unified solutions to those problems. The book provides a lot of information from over a thousand sources in a structured manner to help the reader. The book includes a comprehensive chronology, vocabulary, and bibliography. The author has been a research professor in information engineering for over 25 years. During his career, he became interested in systems thinking, which is closely related to the philosophy and history of science.

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This book brings together key findings, insights, and theories at the intersection of two disciplines – city science and complex systems. It features a curated collection of chapters contributed by emerging scholars conducting cutting-edge research in complexity science, interdisciplinary physics, and quantitative geography. The compendium is tailored to a thematically diverse audience, spanning quantitative fields such as statistical and mathematical physics, as well as socially-focused domains such as geography and urban planning. By integrating novel methods and insights from physics, economics, and geography, this book aims at an interdisciplinary spectrum of graduate students and academic researchers studying cities as complex systems.

More at: link.springer.com