"One of the most exciting theories to emerge from cognitive science research over the past few decades has been Douglas Hofstadter's notion of "strange loops," from Gödel, Escher, Bach (1979). Hofstadter is also an active literary translator who has also written about translation, perhaps most notably in his 1997 book Le Ton Beau de Marot, where he also draws on his cognitive science research. And yet he has never considered the possibility that translation might itself be a strange loop. In this book Douglas Robinson puts Hofstadter's strange-loops theory into dialogue with a series of definitive theories of translation, in the process showing just how cognitively and affectively complex an activity translation actually is"--

One of the most exciting theories to emerge from cognitive science research over the past few decades has been Douglas Hofstadter's notion of “strange loops,” from Gödel, Escher, Bach (1979). Hofstadter is also an active literary translator who has written about translation, perhaps most notably in his 1997 book Le Ton Beau de Marot, where he draws on his cognitive science research. And yet he has never considered the possibility that translation might itself be a strange loop. In this book Douglas Robinson puts Hofstadter's strange-loops theory into dialogue with a series of definitive theories of translation, in the process showing just how cognitively and affectively complex an activity translation actually is.

Argues that the key to understanding ourselves and consciousness is the "strange loop," a special kind of abstract feedback loop that inhabits the brain.

'What is a self and how can a self come out of inanimate matter?' This is the riddle that drove Douglas Hofstadter to write this extraordinary book. In order to impart his original and personal view on the core mystery of human existence - our intangible sensation of 'I'-ness - Hofstadter defines the playful yet seemingly paradoxical notion of 'strange loop', and explicates this idea using analogies from many disciplines.

This book addresses the challenging topic of modeling adaptive networks, which often manifest inherently complex behavior. Networks by themselves can usually be modeled using a neat, declarative, and conceptually transparent Network-Oriented Modeling approach. In contrast, adaptive networks are networks that change their structure; for example, connections in Mental Networks usually change due to learning, while connections in Social Networks change due to various social dynamics. For adaptive networks, separate procedural specifications are often added for the adaptation process. Accordingly, modelers have to deal with a less transparent, hybrid specification, part of which is often more at a programming level than at a modeling level. This book presents an overall Network-Oriented Modeling approach that makes designing adaptive network models much easier, because the adaptation process, too, is modeled in a neat, declarative, and conceptually transparent Network-Oriented Modeling manner, like the network itself. Thanks to this approach, no procedural, algorithmic, or programming skills are needed to design complex adaptive network models. A dedicated software environment is available to run these adaptive network models from their high-level specifications. Moreover, because adaptive networks are described in a network format as well, the approach can simply be applied iteratively, so that higher-order adaptive networks in which network adaptation itself is adaptive (second-order adaptation), too can be modeled just as easily. For example, this can be applied to model metaplasticity in cognitive neuroscience, or second-order adaptation in biological and social contexts. The book illustrates the usefulness of this approach via numerous examples of complex (higher-order) adaptive network models for a wide variety of biological, mental, and social processes. The book is suitable for multidisciplinary Master’s and Ph.D. students without assuming much prior knowledge, although also some elementary mathematical analysis is involved. Given the detailed information provided, it can be used as an introduction to Network-Oriented Modeling for adaptive networks. The material is ideally suited for teaching undergraduate and graduate students with multidisciplinary backgrounds or interests. Lecturers will find additional material such as slides, assignments, and software.

This open access book offers innovative and wide-ranging responses to the continuously flourishing literary phenomenon of autofiction. The book shows the insights that are gained in the shift from the genre descriptor to the adjective, and from a broad application of “the autofictional” as a theoretical lens and aesthetic strategy. In three sections on “Approaches,” “Affordances,” and “Forms,” the volume proposes new theoretical approaches for the study of autofiction and the autofictional, offers fresh perspectives on many of the prominent authors in the discussion, draws them into a dialogue with autofictional practice from across the globe, and brings into view texts, forms, and media that have not traditionally been considered for their autofictional dimensions. The book, in sum, expands the parameters of research on autofiction to date to allow new voices and viewpoints to emerge.

"A brilliant fantasy." -- Manchester Guardian. What would you do if you could re-live your life? In his only novel, occultist P. D. Ouspensky expands upon his concept of eternal recurrence, telling of a man who travels back in time and attempts to correct the mistakes of his schooldays and early manhood, including his romantic misadventures. Set in Moscow and Paris, the story served as an inspiration for the movie Groundhog Day.