An up-to-date overview of the field of connectomics, introducing concepts and mechanisms underlying brain network change at different stages.
The human brain undergoes massive changes during its development, from early childhood and the teenage years to adulthood and old age. Across a wide range of species, from C. elegans and fruit flies to mice, monkeys, and humans, information about brain connectivity (connectomes) at different stages is now becoming available. New approaches in network neuroscience can be used to analyze the topological, spatial, and dynamical organization of such connectomes. In Changing Connectomes, Marcus Kaiser provides an up-to-date overview of the field of connectomics and introduces concepts and mechanisms underlying brain network changes during evolution and development.

Drawing on a range of results from experimental, clinical, and computational studies, Kaiser describes changes during healthy brain maturation and during brain network disorders (including such neurodevelopmental conditions as schizophrenia and depression), brain injury, and neurodegenerative disorders including dementia. He argues that brain stimulation is an area where understanding connectome development could help in assessing long-term effects of interventions. Changing Connectomes is a suitable starting point for researchers who are new to the field of connectomics, and also for researchers who are interested in the link between brain network organization and brain and cognitive development in health and disease. Matlab/Octave code examples available at the MIT Press website will allow computational neuroscience researchers to understand and extend the shown mechanisms of connectome development.

Source: www.amazon.com

With the recent developments in computing technologies and the thriving research scene in Complexity Science, economists and other social scientists have become aware of a more flexible and promising alternative for modelling socioeconomic systems; one that, in contrast with neoclassical economics, advocates for the realism of the assumptions, the importance of context and culture, the heterogeneity of agents (individuals or organisations), and the bounded rationality of individuals who behave and learn in multifaceted ways in uncertain environments. The book synthesises an extensive body of work in the field of social complexity and constructs a unifying framework that allows developing concrete applications to important socioeconomic problems. This one-of-a-kind textbook provides a comprehensive panorama for advanced undergraduates and graduate students who want to become familiar with a wide range of issues related to social complexity. It is also a pioneering text that can support professors who wish to learn techniques and produce research in this novel field.
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After reviewing the main concepts, premises and implications of complexity theory, the book frames this vision within the history of economic thought. Then, it articulates a meta-theory in which interdependent agents are embedded in a social context and whose collective and decentralised behaviour generates socio-economic phenomena. Such a framework builds on theories from evolutionary, institutional and behavioural economics, as well as analytical sociology. The book then reviews different computational tools for modelling complex adaptive systems, such as cellular automata, networks, and agent-based models. It elaborates on their analytical advantages in comparison to equation-based models, and how they can be calibrated/estimated and validated with empirical data. Finally, the book advocates for the practical use of these computational tools and makes a case for policy applications and the study of causal mechanisms.

Source: www.social-complexity.com

Source: www.amazon.com

Taylor, Tim, Dorin, Alan

Is it possible to design robots and other machines that can reproduce and evolve? And, if so, what are the implications: for the machines, for ourselves, for our environment, and for the future of life on Earth and elsewhere?
In this book the authors provide a chronological survey and comprehensive archive of the early history of thought about machine self-reproduction and evolution. They discuss contributions from philosophy, science fiction, science and engineering, and uncover many examples that have never been discussed in the Artificial Intelligence and Artificial Life literature before now. In the final chapter they provide a synthesis of the concepts discussed, offer their views on the field’s future directions, and call for a broad community discussion about the significant implications of intelligent evolving machines.
The book will be of interest to general readers, and a valuable resource for researchers, practitioners, and historians engaged with ideas in artificial intelligence, artificial life, robotics, and evolutionary computing.

Source: www.springer.com

Editors: Josh Bongard, Juniper Lovato, Laurent Hebert-Dufrésne, Radhakrishna Dasari and Lisa Soros

This volume presents the proceedings of the 2020 Conference on Artificial Life (ALIFE 2020) which took place online July 13-18. Originally scheduled to be held in Montreal, Canada, this was the first time our conference had been conducted in this manner. Of course, our community was not alone: just about every human community has had to adapt to the covid-19 pandemic and its repercussions. It is difficult to avoid seeing the irony in this: Artificial Life researchers have declared, since the field’s inception at a small workshop at Los Alamos in 1987, that we wish to understand how life adapts to unforeseen circumstances. Further, we wish to incorporate learned mechanisms of adaptation into our technologies and, possibly, our societies. Put simply, Artificial Life invites us to think and learn about adaptation; SARS-CoV-2 forces us to adapt. More simple yet: ALife is theory; COVID is practice. There is a long tradition in our field of peering at our computer screens or into our petri dishes, waiting with bated breath to see what new forms emerge. Likewise for the post-pandemic world. Whatever does emerge from the conference, and from the pandemic — and whether we learn from it, and whether we use that knowledge to benefit each other — it is our honor to be part of the adventure with you.

Source: www.mitpressjournals.org