Hosftadter and his colleagues at The Fluid Analogies Research Group have developed computer models that help describe and explain human discovery, creation and analogical thought. The key issue of perception is investigated through the exploration of playful anagrams, number puzzles, word play and fanciful alphabetical styles, and the result is a survey of cognitive processes. This text presents the results.

Describes research projects in cognitive science over the past twenty years, and discusses arithmetical play, analogy, research evaluation, and creativity

Shows how analogy-making pervades human thought at all levels, influencing the choice of words and phrases in speech, providing guidance in unfamiliar situations, and giving rise to great acts of imagination.

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

Hofstadter has developed a sophisticated vision of the mind in which perception, at an abstract level, is the key.

The psychologist William James observed that "a native talent for perceiving analogies is... the leading fact in genius of every order." The centrality and the ubiquity of analogy in creative thought have been noted again and again by scientists, artists, and writers, and understanding and modeling analogical thought have emerged as two of the most important challenges for cognitive science.Analogy-Making as Perception is based on the premise that analogy-making is fundamentally a high-level perceptual process in which the interaction of perception and concepts gives rise to "conceptual slippages" which allow analogies to be made. It describes Copycat - a computer model of analogymaking, developed by the author with Douglas Hofstadter, that models the complex, subconscious interaction between perception and concepts that underlies the creation of analogies.In Copycat, both concepts and high-level perception are emergent phenomena, arising from large numbers of low-level, parallel, non-deterministic activities. In the spectrum of cognitive modeling approaches, Copycat occupies a unique intermediate position between symbolic systems and connectionist systems a position that is at present the most useful one for understanding the fluidity of concepts and high-level perception.On one level the work described here is about analogy-making, but on another level it is about cognition in general. It explores such issues as the nature of concepts and perception and the emergence of highly flexible concepts from a lower-level "subcognitive" substrate.Melanie Mitchell, Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan, is a Fellow of the Michigan Society of Fellows. She is also Director of the Adaptive Computation Program at the Santa Fe Institute.

Hofstadter's collection of quirky essays is unified by its primary concern: to examine the way people perceive and think.

Stan Franklin is the perfect tour guide through the contemporary interdisciplinary matrix of artificial intelligence, cognitive science, cognitive neuroscience, artificial neural networks, artificial life, and robotics that is producing a new paradigm of mind. Along the way, Franklin makes the case for a perspective that rejects a rigid distinction between mind and non-mind in favor of a continuum from less to more mind.

Lost in an art—the art of translation. Thus, in an elegant anagram (translation = lost in an art), Pulitzer Prize-winning author and pioneering cognitive scientist Douglas Hofstadter hints at what led him to pen a deep personal homage to the witty sixteenth-century French poet Clément Marot.”Le ton beau de Marot” literally means ”The sweet tone of Marot”, but to a French ear it suggests ”Le tombeau de Marot”—that is, ”The tomb of Marot”. That double entendre foreshadows the linguistic exuberance of this book, which was sparked a decade ago when Hofstadter, under the spell of an exquisite French miniature by Marot, got hooked on the challenge of recreating both its sweet message and its tight rhymes in English—jumping through two tough hoops at once.In the next few years, he not only did many of his own translations of Marot's poem, but also enlisted friends, students, colleagues, family, noted poets, and translators—even three state-of-the-art translation programs!—to try their hand at this subtle challenge.The rich harvest is represented here by 88 wildly diverse variations on Marot's little theme. Yet this barely scratches the surface of Le Ton beau de Marot, for small groups of these poems alternate with chapters that run all over the map of language and thought.Not merely a set of translations of one poem, Le Ton beau de Marot is an autobiographical essay, a love letter to the French language, a series of musings on life, loss, and death, a sweet bouquet of stirring poetry—but most of all, it celebrates the limitless creativity fired by a passion for the music of words.Dozens of literary themes and creations are woven into the picture, including Pushkin's Eugene Onegin, Dante's Inferno, Salinger's Catcher in the Rye, Villon's Ballades, Nabokov's essays, Georges Perec's La Disparition, Vikram Seth's Golden Gate, Horace's odes, and more.Rife with stunning form-content interplay, crammed with creative linguistic experiments yet always crystal-clear, this book is meant not only for lovers of literature, but also for people who wish to be brought into contact with current ideas about how creativity works, and who wish to see how today's computational models of language and thought stack up next to the human mind.Le Ton beau de Marot is a sparkling, personal, and poetic exploration aimed at both the literary and the scientific world, and is sure to provoke great excitement and heated controversy among poets and translators, critics and writers, and those involved in the study of creativity and its elusive wellsprings.

Is human creativity a wall that AI can never scale? Many people are happy to admit that experts in many domains can be matched by either knowledge-based or sub-symbolic systems, but even some AI researchers harbor the hope that when it comes to feats of sheer brilliance, mind over machine is an unalterable fact. In this book, the authors push AI toward a time when machines can autonomously write not just humdrum stories of the sort seen for years in AI, but first-rate fiction thought to be the province of human genius. It reports on five years of effort devoted to building a story generator--the BRUTUS.1 system. This book was written for three general reasons. The first theoretical reason for investing time, money, and talent in the quest for a truly creative machine is to work toward an answer to the question of whether we ourselves are machines. The second theoretical reason is to silence those who believe that logic is forever closed off from the emotional world of creativity. The practical rationale for this endeavor, and the third reason, is that machines able to work alongside humans in arenas calling for creativity will have incalculable worth.