M. T. Mitchell

What enables individually simple insects like ants to act with such precision and purpose as a group? How do trillions of individual neurons produce something as extraordinarily complex as consciousness? What is it that guides self-organizing structures like the immune system, the World Wide Web, the global economy, and the human genome? These are just a few of the fascinating and elusive questions that the science of complexity seeks to answer. In this remarkably accessible and companionable book, leading complex systems scientist Melanie Mitchell provides an intimate, detailed tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. Comprehending such systems requires a wholly new approach, one that goes beyond traditional scientific reductionism and that re-maps long-standing disciplinary boundaries. Based on her work at the Santa Fe Institute and drawing on its interdisciplinary strategies, Mitchell brings clarity to the workings of complexity across a broad range of biological, technological, and social phenomena, seeking out the general principles or laws that apply to all of them. She explores as well the relationship between complexity and evolution, artificial intelligence, computation, genetics, information processing, and many other fields. Richly illustrated and vividly written, Complexity : A Guided Tour offers a comprehensive and eminently comprehensible overview of the ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for the field's contribution to solving some of the most important scientific questions of our time.

In this paper I focus on the central role faith plays in the thought of Polanyi and Voegelin. I begin by indicating how both find the modern conception of scientific knowing seriously wanting. What Polanyi terms "objectivism" and Voegelin calls "scientism" is the modern tendency to reduce knowledge to only that which can be scientifically demonstrated. This errant view of knowledge does not occur in a vacuum, though, and both men draw a connection between this and the political pathologies of the twentieth century. I then show the complementary ways in which these two thinkers believe recovery is possible: an epistemological solution encompassed in Polanyi's personal knowledge and an ontological reorientation that is the core of Voegelin's insistence that we must recover an awareness of human participation in transcendent reality

The polymath Michael Polanyi first made his mark as a physical chemist, but his interests gradually shifted to economics, politics, and philosophy, in which field he would ultimately propose a revolutionary theory of knowledge that grew out of his firsthand experience with both the scientific method and political totalitarianism. In this sixth entry in ISI Books’ Library of Modern Thinkers’ series, Mark T. Mitchell reveals how Polanyi came to recognize that the roots of the modern political and spiritual crisis lay in an errant conception of knowledge that served to foreclose any possibility of making meaningful statements about truth, goodness, or beauty. Polanyi’s theory of knowledge as ineluctably personal but also grounded in reality is not merely of historical interest, writes Mitchell, for it proposes an attractive alternative for anyone who would reject both the hubris of modern rationalism and the ultimately nihilistic implications of academic postmodernism

Alexithymia is associated with emotion processing deficits, particularly for negative emotional information. However, also common are a high prevalence of somatic symptoms and the perception of somatic sensations as distressing. Although little research has yet been conducted on memory in alexithymia, we hypothesized a paradoxical effect of alexithymia on memory. Specifically, recall of negative emotional words was expected to be reduced in alexithymia, while memory for illness words was expected to be enhanced in alexithymia.Eighty-five high or low alexithymia participants viewed and rated arousing illness-related , emotionally positive , negative , and neutral words . Recall was assessed 45 min later.High alexithymia participants recalled significantly fewer negative emotion words but also more illness-related words than low alexithymia participants. The results suggest that personal relevance can shape cognitive processing of stimuli, even to enhance retention of a subclass of stimuli whose retention is generally impaired in alexithymia

The dynamics/computation debate recalls a similar debate in the evolutionary biology community concerning the relative primacy of theories of structure versus theories of change. A full account of cognition will require a rapprochement between such theories and will include both computational and dynamical notions. The key to making computation relevant to cognition is not making it analog, but rather understanding how functional information-processing structures can emerge in complex dynamical systems.

Moderate physiological or emotional arousal induced after learning modulates memory consolidation, helping to distinguish important memories from trivial ones. Yet, the contribution of subjective awareness or interpretation of arousal to this effect is uncertain. Alexithymia, which is an inability to describe or identify one’s emotional and arousal states even though physiological responses to arousal are intact, provides a tool to evaluate the role of arousal interpretation. Participants scoring high and low on alexithymia learned a list of 30 words, followed by immediate recall. Participants then saw either an arousing or neutral video . Memory was tested 24-h later. Physiological response to arousal was comparable between groups, but subjective response to arousal was impaired in high alexithymia. Yet, delayed word recognition was enhanced by arousal regardless of alexithymia status. Thus, subjective response to arousal, i.e., cognitive appraisal, was not necessary for memory modulation to occur

This paper argues for the possibility of 'artificial life' and computational evolution, first by discussing (via a highly simplified version) John von Neumann's self-reproducing automaton and then by presenting some recent work focusing on computational evolution, in which 'cellular automata', a form of parallel and decentralized computing system, are evolved via 'genetic algorithms'. It is argued that such in silico experiments can help to make sense of the question of whether we can eventually build computers that are intelligent and alive

This paper studies the properties and performance of models for estimating local probability distributions which are used as components of larger probabilistic systems — history-based generative parsing models. We report experimental results showing that memory-based learning outperforms many commonly used methods for this task (Witten-Bell, Jelinek-Mercer with fixed weights, decision trees, and log-linear models). However, we can connect these results with the commonly used general class of deleted interpolation models by showing that certain types of memory-based learning, including the kind that performed so well in our experiments, are instances of this class. In addition, we illustrate the divergences between joint and conditional data likelihood and accuracy performance achieved by such models, suggesting that smoothing based on optimizing accuracy directError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMaply might greatly improve performance.

This book is a collection of essays exploring adaptive systems from many perspectives, ranging from computational applications to models of adaptation in living and social systems. The essays on computation discuss history, theory, applications, and possible threats of adaptive and evolving computations systems. The modeling chapters cover topics such as evolution in microbial populations, the evolution of cooperation, and how ideas about evolution relate to economics. The title Perspectives on Adaptation in Natural and Artificial Systems honors John Holland, whose 1975 Book, Adaptation in Natural and Artificial Systems has become a classic text for many disciplines in which adaptation play a central role. The essays brought together here were originally written to honor John Holland, and span most of the different areas touched by his wide-ranging and influential research career. The authors include some of the most prominent scientists in the fields of artificial intelligence evolutionary computation, and complex adaptive systems. Taken together, these essays present a broad modern picture of current research on adaptation as it relates to computers, living systems, society, and their complex interactions.

This book is a collection of essays exploring adaptive systems from many perspectives, ranging from computational applications to models of adaptation in living and social systems. The essays on computation discuss history, theory, applications, and possible threats of adaptive and evolving computations systems. The modeling chapters cover topics such as evolution in microbial populations, the evolution of cooperation, and how ideas about evolution relate to economics. The title Perspectives on Adaptation in Natural and Artificial Systems honors John Holland, whose 1975 Book, Adaptation in Natural and Artificial Systems has become a classic text for many disciplines in which adaptation play a central role. The essays brought together here were originally written to honor John Holland, and span most of the different areas touched by his wide-ranging and influential research career. The authors include some of the most prominent scientists in the fields of artificial intelligence evolutionary computation, and complex adaptive systems. Taken together, these essays present a broad modern picture of current research on adaptation as it relates to computers, living systems, society, and their complex interactions.

Cannabis sativa L. is grown and marketed under a large number of named strains. Strains are often associated with phenotypic traits of interest to consumers, such as aroma and cannabinoid content. Yet genetic inconsistencies have been noted within named strains. We asked whether genetically inconsistent samples of a commercial strain also display inconsistent aroma profiles. We genotyped 32 samples using variable microsatellite regions to determine a consensus strain genotype and identify genetic outliers for four strains. Results were used to select 15 samples for olfactory testing. A genetic outlier sample was available for all but one strain. Aroma profiles were obtained by 55 sniff panelists using quantitative sensory evaluation of 40 odor descriptors. Within a strain, aroma descriptor frequencies for the genetic outlier were frequently at odds with those of the consensus samples. It appears that within-strain genetic differences are associated with differences in aroma profile. Because these differences were perceptible to untrained panelists, they may also be noticed by retail consumers. Our results could help the cannabis industry achieve better control of product consistency.

At its core, natural law theory claims that certain moral truths exist and are known, in varying degrees, by all rational persons. While I agree with this general statement, it is my contention that we must re-examine the manner in which the precepts of natural law are known. It is frequently assumed that any theory of natural law must presuppose the possibility of tradition-independent rationality whereby each rational person can directly access universal moral truths; the ability of each person to know moral truth in a rationally autonomous fashion without dependence on such things as authority, submission, and trust; and the explicit nature of moral knowing, whereby the precepts of natural law admit of full articulation. These three presuppositions must be reconsidered. Three twentieth-century thinkers who have, in different ways, attempted to overcome what they perceive to be an errant understanding of knowledge are Michael Oakeshott, Alasdair MacIntyre, and Michael Polanyi. While only MacIntyre claims to be a natural law thinker, the insights provided by all three, especially Polanyi, provide the conceptual tools necessary for a new understanding of natural law theory. Such a reconceptualization will, like traditional natural law, affirm the existence of moral truth grounded in an essential human nature. But in addition, this approach will appreciate what I term the epistemic role of tradition, which shows that a tradition-independent theory of knowledge is philosophically incoherent; the necessity of authority, submission, and trust, without which knowing cannot occur; the indispensable role played by tacit knowledge. Because reality is only provisionally knowable, moral inquiry is an on-going effort better to comprehend the moral truth to which we are responsible