Bøger af Rodrick Wallace

The relentless march toward massively parallel 'Self-X' machines that must program, protect, and repair themselves while managing critical phenomena raises questions of safety and stability. What are the failure modes of the new machines that will direct nuclear reactors, power grids, air traffic control and large-scale financial transactions? Is 'graceful degradation under stress' a realistic expectation? Study of animal cognition suggests that evolution has had only modest success stabilizing individual minds and formal analysis shows that both sudden and subtle failures in massively parallel cognitive structures are norms: Such devices are inherently as difficult to stabilize as to program. Implications for the design of critical systems are starkly troubling.

The creation of economic institutions that can function under the impact of substantial 'non-quantifiable' risks is analogous to the dilemmas confronting our hunter-gatherer forefathers in the face of large-scale ecological uncertainties. The ultimate solution was not a super hunter-gatherer technology that could ride out repeated catastrophe, but the invention, in neolithic times, of culturally-adapted 'farmed' ecosystems constructed to maximize food yield and minimize risks of famine. This book applies evolutionary and ecosystem theory to the design of culturally-specific farmed economies, recognizing the impossibility of a one-size-fits-all system. The tools used are powerful new statistical models abducted from Shannon's communication theory that are well-suited to data analysis.

From the ¿punctuated equilibrium' of Eldrege and Gould, through Lewontin's ¿triple helix' and the various visions and revisions of the Extended Evolutionary Synthesis (EES) of Laland and others, both data and theory have demanded an opening-up of the 1950's Evolutionary Synthesis that so firmly wedded evolutionary theory to the mathematics of gene frequency analysis. It can, however, be argued that a single deep and comprehensive mathematical theory may simply not be possible for the almost infinite varieties of evolutionary process active at and across the full range of scales of biological, social, institutional, and cultural phenomena. Indeed, the case history of 'meme theory' should have raised a red flag that narrow gene-centered models of evolutionary process may indeed have serious limitations. What is attempted here is less grand, but still broader than a gene-centered analysis. Following the instruction of Maturana and Varela that all living systems are cognitive, in a certainsense, and that living as a process is a process of cognition, the asymptotic limit theorems of information and control theories that bound all cognition provide a basis for constructing an only modestly deep but wider-ranging series of probability models that might be converted into useful statistical tools for the analysis of observational and experimental data related to evolutionary process. The line of argument in this series of interrelated essays proves to be surprisingly direct.

This book applies cutting-edge methods from cognitive and evolutionary theories to develop models of conflict between hierarchically-structured cognitive entities under circumstances of imprecision, uncertainty and stress.

The vector-borne Zika virus joins avian influenza, Ebola, and yellow fever as recent public health crises threatening pandemicity.By a combination of stochastic modeling and economic geography, this book proposes two key causes together explain the explosive spread of the worst of the vector-borne outbreaks.Ecosystems in which such pathogens are largely controlled by environmental stochasticity are being drastically streamlined by both agribusiness-led deforestation and deficits in public health and environmental sanitation.Consequently, a subset of infections that once burned out relatively quickly in local forests are now propagating across susceptible human populations whose vulnerability to infection is often exacerbated in structurally adjusted cities. The resulting outbreaks are characterized by greater global extent, duration, and momentum.As infectious diseases in an age of nation states and global health programs cannot, as much of the present modeling literature presumes, be described by interacting populations of host, vector, and pathogen alone, a series of control theory models is also introduced here. These models, useful to researchers and health officials alike, explicitly address interactions between government ministries and the pathogens they aim to control.

The language of business is the language of dreams, but the language of war is the language of nightmare made real.

RTW states on average and median have lower life expectancy, higher obesity prevalence, and higher rates of all-cause mortality, early mortality from chronic conditions, child mortality, and risk behaviors than non-RTW states.

The asymptotic limit theorems of control and information theories make it possible to explore the dynamics of collapse likely to afflict large-scale systems of autonomous ground vehicles that communicate with each other and with an embedding intelligent roadway.

This volume examines a class of probability models describing how epigenetic context affects gene expression and organismal development, using the asymptotic limit theorems of information theory in a highly formal manner.

This book explores mental disorders from a uniquely evolutionary perspective.

An earlier book by Rodrick Wallace entitled Consciousness: A Mathematical Treatment of the Global Neuronal Workspace Model, introduced a formal information-theoretic approach to individual consciousness. This latest book takes a more formal 'groupoid' perspective to its predecessor and generalizes the results presented in that earlier book.

Invoking an obvious canonical homology with statistical physics, the method, when iterated in the spirit of the Hierarchical Linear Model of regression theory, generates a fluctuating dynamic threshold for consciousness which is similar to a tunable phase transition in a physical system.

This volume examines a class of probability models describing how epigenetic context affects gene expression and organismal development, using the asymptotic limit theorems of information theory in a highly formal manner.

This book introduces a cutting-edge mathematical formalism based on the asymptotic limit theorems of information theory to describe how punctuated shifts in mesoscale ecosystems can entrain patterns of gene expression and organismal evolution.