Hierarchical complexity's unidimensional measurement can help rectify policy confusion and debates about democratization and terrorism reduction. Stages of political development examined using the method yield task analyses demonstrating why stages cannot be skipped or rushed. Composites of stages and societies' transitions implicate policy change for anti-corruption and nation-building. New indexes for the political domain should be developed using hierarchical complexity to account for and measure a multitude of political tasks regardless of content or context. Measurement offers (...) a reliable, empirical basis to resist attempts to rush development. Hierarchical complexity accounts for why such efforts are doomed in advance to fail. (shrink)

Evolution means different things at different stages of development. Higher stage explanations for it are downward assimilated at lower stages. Different scientific explanations for evolution also reflect different stages of development. Hierarchical complexity of tasks in evolution is a behavioral analytic explanation. It is selection processes of various kinds in tandem with changes in selection tasks' orders of hierarchical complexity. There is neither teleology nor evolutionary favoring of the highest stages of performance. Selection tasks at higher (...) orders of complexity increasingly decenter at all scales of behaviors from thought to history's social periods. These processes account for sociopolitical conflicts over evolution. (shrink)

Critical consideration is given the empirical evidence for psychological models of religious development, its supposed relationship to other domains of psychological development, and especially, moral development. Significant problems with stage conceptions in these models augur a fundamental rethinking of religious development as a construct in developmental psychology. Model of Hierarchical Complexity has demonstrable promise for enabling greater precision in constructs and methods. This may resolve some central problems and advance research in the field.

The institutionalization of systems of informed consent in market economies has exaggerated rather than minimized the meritocractic effect of such economies. In developing economies, it may help reduce both inherent economic gaps and effects of inherited wealth. In both cases, the highest paid people are those whose performances evidence the highest hierarchical complexity, and lowest paid people have the lowest stages of performance. Society is stratified according to stage of performance. Postformal thought is more likely to develop in (...) graduate level education. Higher education has the effect of further stratifying individuals by stage of performance, rather than equalizing opportunity. (shrink)

The Model of Hierarchical Complexity is introduced in terms of its main concepts, background, and applications. As a general, quantitative behavioral developmental theory, the Model enables examination of universal patterns of evolution and development. Behavioral tasks are definable and their organization of information in increasingly greater hierarchical, or vertical, complexity is measurable. Fifteen orders of hierarchical complexity account for task performances across domains, ranging from those of machines to creative geniuses. The four most complex (...) orders are demonstrated by postformal stages of thought, which measure beyond formal operations, the highest stage found by Piaget for adults. (shrink)

We distinguish traditional cognition theories from hierarchically complex stacked neural networks that meet many of Newell's criteria. The latter are flexible and can learn anything that a person can learn, by using their mistakes and successes the same way humans do. Shortcomings are due largely to limitations of current technology.

Empirical evidence has demonstrated the validity and reliability of moral development instruments such as the Defining Issues Test (DIT) and Moral Judgment Test (MJT). Rasch item reliability for each was .95. A newer instrument generated using the Model of Hierarchical Complexity had item reliability of .97. Rasch scores of responses to each instruments' items correlated well with the items' measure of hierarchical complexity, r = .286, .372, .557, .767. Test items used to measure moral reasoning were (...) significantly correlated. In general, stage of moral development did not predict political affiliation or voting, supporting Kohlberg's claim that structure, not content, underlies stage. (shrink)

Individuals do not operate “at a stage of development.” They operate at a range of different levels of hierarchical complexity depending on skill area, task, context, degree of support, and other variables. It is thus necessary to postulate the concept of domain to refer to the particular conceptual, behavioral, or affective area within which activity operates. The concept raises questions and implications for theory building and application. Such issues are elaborated by discussing a variety of domains and social (...) contexts. A postformal case example of leadership in higher education illuminates the concept of domains and the interrelationships among domains. (shrink)

The missing ingredients in efforts to develop neural networks and artificial intelligence (AI) that can emulate human intelligence have been the evolutionary processes of performing tasks at increased orders of hierarchical complexity. Stacked neural networks based on the Model of Hierarchical Complexity could emulate evolution's actual learning processes and behavioral reinforcement. Theoretically, this should result in stability and reduce certain programming demands. The eventual success of such methods begs questions of humans' survival in the face of (...) androids of superior intelligence and physical composition. These raise future moral questions worthy of speculation. (shrink)

(2008). Editors' Introduction to the Special Issue on Postformal Thought and Hierarchical Complexity. World Futures: Vol. 64, Postformal Thought and Hierarchical Complexity, pp. 297-304.

The formal theory of the Model of Hierarchical Complexity is presented. Complexity theories generally exclude the concept of hierarchical complexity; Developmental Psychology has included it for over 20 years. It also applies to social systems and non-human systems. Formal axioms for the Model are outlined. The model assigns an order of hierarchical complexity to every task, using natural numbers, establishing a quantal notion of stage and stages of performance. This formalizes properties of stage (...) theories in psychology. The formal theory of the model enables extending the concept of hierarchical complexity to any field where tasks and their performances exist. (shrink)

This chapter argues that the multilevel selection -1 to MLS-2 model of a major transition is incomplete because it overlooks a crucial component of fitness. It addresses that the evolution of individuality literature has failed to account for expansive fitness and that expansive fitness differences play an important role in the transition to regimes sensitive to the fitness of the corporate agent. It discusses multilevel evolution during the three phases of transitions in individuality: the aggregate phase, the group phase, and (...) the individual phase. This chapter shows that the path a lineage takes through the phases of transitions is not fixed, but determined by ecology. (shrink)

This is a comprehensive discussion of complexity as it arises in physical, chemical, and biological systems, as well as in mathematical models of nature. Common features of these apparently unrelated fields are emphasised and incorporated into a uniform mathematical description, with the support of a large number of detailed examples and illustrations. The quantitative study of complexity is a rapidly developing subject with special impact in the fields of physics, mathematics, information science, and biology. Because of the variety (...) of the approaches, no comprehensive discussion has previously been attempted. This book will be of interest to graduate students and researchers in physics (nonlinear dynamics, fluid dynamics, solid-state, cellular automata, stochastic processes, statistical mechanics and thermodynamics), mathematics (dynamical systems, ergodic and probability theory), information and computer science (coding, information theory and algorithmic complexity), electrical engineering and theoretical biology. (shrink)

The target and background will change continuously in the long-term tracking process, which brings great challenges to the accurate prediction of targets. The correlation filter algorithm based on manual features is difficult to meet the actual needs due to its limited feature representation ability. Thus, to improve the tracking performance and robustness, an improved hierarchical convolutional features model is proposed into a correlation filter framework for visual object tracking. First, the objective function is designed by lasso regression modeling, and (...) a sparse, time-series low-rank filter is learned to increase the interpretability of the model. Second, the features of the last layer and the second pool layer of the convolutional neural network are extracted to realize the target position prediction from coarse to fine. In addition, using the filters learned from the first frame and the current frame to calculate the response maps, respectively, the target position is obtained by finding the maximum response value in the response map. The filter model is updated only when these two maximum responses meet the threshold condition. The proposed tracker is evaluated by simulation analysis on TC-128/OTB2015 benchmarks including more than 100 video sequences. Extensive experiments demonstrate that the proposed tracker achieves competitive performance against state-of-the-art trackers. The distance precision rate and overlap success rate of the proposed algorithm on OTB2015 are 0.829 and 0.695, respectively. The proposed algorithm effectively solves the long-term object tracking problem in complex scenes. (shrink)

One of the most important methods in dealing with the optimization of large, complex systems is that of hierarchical decomposition. The idea is to reduce the overall complex problem into manageable approximate problems or subproblems, to solve these problems, and to construct a solution of the original problem from the solutions of these simpler prob lems. Development of such approaches for large complex systems has been identified as a particularly fruitful area by the Committee on the Next Decade in (...) Operations Research (1988) [42] as well as by the Panel on Future Directions in Control Theory (1988) [65]. Most manufacturing firms are complex systems characterized by sev eral decision subsystems, such as finance, personnel, marketing, and op erations. They may have several plants and warehouses and a wide variety of machines and equipment devoted to producing a large number of different products. Moreover, they are subject to deterministic as well as stochastic discrete events, such as purchasing new equipment, hiring and layoff of personnel, and machine setups, failures, and repairs. (shrink)

An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in (...) divergent explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

During the first two years of human life a common neural substrate underlies the hierarchical organization of elements in the development of speech as well as the capacity to combine objects manually, including tool use. Subsequent cortical differentiation, beginning at age two, creates distinct, relatively modularized capacities for linguistic grammar and more complex combination of objects. An evolutionary homologue of the neural substrate for language production and manual action is hypothesized to have provided a foundation for the evolution of (...) language before the divergence of the hominids and the great apes. Support comes from the discovery of a Broca's area homologue and related neural circuits in contemporary primates. In addition, chimpanzees have an identical constraint on hierarchical complexity in both tool use and symbol combination. Their performance matches that of the two-year-old child who has not yet developed the neural circuits for complex grammar and complex manual combination of objects. (shrink)

To explain social learning without invoking the cognitively complex concept of imitation, many learning mechanisms have been proposed. Borrowing an idea used routinely in cognitive psychology, we argue that most of these alternatives can be subsumed under a single process, priming, in which input increases the activation of stored internal representations. Imitation itself has generally been seen as a This has diverted much research towards the all-or-none question of whether an animal can imitate, with disappointingly inconclusive results. In the great (...) apes, however, voluntary, learned behaviour is organized hierarchically. This means that imitation can occur at various levels, of which we single out two clearly distinct ones: the a rather detailed and linear specification of sequential acts, and the a broader description of subroutine structure and the hierarchical layout of a behavioural Program level imitation is a high-level, constructive mechanism, adapted for the efficient learning of complex skills and thus not evident in the simple manipulations used to test for imitation in the laboratory. As examples, we describe the food-preparation techniques of wild mountain gorillas and the imitative behaviour of orangutans undergoing to the wild. Representing and manipulating relations between objects seems to be one basic building block in their hierarchical programs. There is evidence that great apes suffer from a stricter capacity limit than humans in the hierarchical depth of planning. We re-interpret some chimpanzee behaviour previously described as and suggest that all great apes may be able to imitate at the program level. Action level imitation is seldom observed in great ape skill learning, and may have a largely social role, even in humans. (shrink)

The existential insecurity of human beings has induced them to create protective spheres of symbols: myths, religions, values, belief systems, theories, etc. Rationality is one of the key factors contributing to the construction of civilisation in technical and symbolic terms. As Hankiss (2001) has emphasised, protective spheres of symbols may collapse – thus causing a profound social crisis. Social and political transformations had a tremendous impact at the end of the 20th century. As a result, management theories have been revised (...) in order to deal with transition and uncertainty. Francis Fukuyama's (2000) approach is supportive of hierarchical organisation as the best solution when facing a 'disruption'. The notion of Homo Hierarchicus has been based on, allegedly, rational presumptions. This paper contributes to the discussion on hierarchy within contemporary organisations. It criticises so-called 'natural' and 'rational' necessities justifying hierarchy. A key issue identified by the paper is the formalisation of language in claiming value-free knowledge and 'detached' observation as the basis for neutral rationality and aspired efficiency. This should be seriously reconsidered as hindering rather than aiding understanding of social complexity. All in all, Homo Hierarchicus appears to be misleading rather than helping symbolic sphere or construct. (shrink)

This article discusses the proof theory, semantics and meta-theory of a class of adaptive logics, called hierarchic adaptive logics. Their specific characteristics are illustrated throughout the article with the use of one exemplary logic HKx, an explicans for reasoning with prioritized belief bases. A generic proof theory for these systems is defined, together with a less complex proof theory for a subclass of them. Soundness and a restricted form of completeness are established with respect to a non-redundant semantics. It is (...) shown that all hierarchic adaptive logics are reflexive, have the strong reassurance property and that a subclass of them is a fixed point for a broad class of premise sets. Finally, they are compared to a different yet related class of adaptive logics. (shrink)

This paper compares the two known logical forms of hierarchy, both of which have been used in models of natural phenomena, including the biological. I contrast their general properties, internal formal relations, modes of growth (emergence) in applications to the natural world, criteria for applying them, the complexities that they embody, their dynamical relations in applied models, and their informational relations and semiotic aspects.

Recognized as a simple communicative behavior, referential pointing is cognitively complex because it invites a communicator to consider an addressee's knowledge. Although we know referential pointing is affected by addressees’ physical location, it remains unclear whether and how communicators’ inferences about addressees’ mental representation of the interaction space influence sensorimotor control of referential pointing. The communicative perspective-taking task requires a communicator to point at one out of multiple referents either to instruct an addressee which one should be selected (communicative, COM) (...) or to predict which one the addressee will select (non-communicative, NCOM), based on either which referents can be seen (Level-1 perspective-taking, PT1) or how the referents were perceived (Level-2 perspective-taking, PT2) by the addressee. Communicators took longer to initiate the movements in PT2 than PT1 trials, and they held their pointing fingers for longer at the referent in COM than NCOM trials. The novel findings of this study pertain to trajectory control of the pointing movements. Increasing both communicative and perspective-taking demands led to longer pointing trajectories, with an under-additive interaction between those two experimental factors. This finding suggests that participants generate communicative behaviors that are as informative as required rather than overly exaggerated displays, by integrating communicative and perspective-taking information hierarchically during sensorimotor control. This observation has consequences for models of human communication. It implies that the format of communicative and perspective-taking knowledge needs to be commensurate with the movement dynamics controlled by the sensorimotor system. (shrink)

The formation mechanism of innovation networks is one of the core issues in the current research of innovation networks, and proximity plays an important role in the formation and development of innovation networks; however, which proximity is more important and how different proximities interact remain to be further researched. This study conducts a social network analysis and adopts a spatial interaction model to examine innovation networks among 290 Chinese cities. The results reveal that, first, the hierarchical characteristics of Chinese (...) cities’ innovation networks reflect a core periphery structure and the spatial patterns of large dispersion and small agglomeration. Further, bound by the Hu line, the hierarchy is high in the east and low in the west. Second, geographical, institutional, and cognitive proximities positively affect Chinese cities’ innovation networking. Cognitive proximity, particularly, has the highest impact. Geographical proximity reinforces the effect of institutional proximity, and thus, their interactions are complementary. (shrink)

Levels of reality reflect one kind of complexity, which can be modeled using a specification hierarchy. Levels emerged during the Big Bang, as physical degrees of freedom became increasingly fixed as the expanding universe developed, and new degrees of freedom associated with higher levels opened up locally, requiring new descriptive semantics. History became embodied in higher level entities, which are increasingly individuated, aggregate patterns of lower level entities. Development is an epigenetic trajectory from vaguer to more definite and individuated (...) embodiment, punctuated by the emergence of new integrative levels. It is constrained by being subsumed by lower levels (e.g., physical dynamics) and may be guided by structural attractors as well as by internally stored information (e.g., genes) in the higher levels. I conjecture, on a thermodynamic basis, that the number of levels that become manifest in an expanding universe depends upon its rate of expansion. (shrink)

A system as complex as man can be viewed from many sides, and the one or the other axis can be selected to form a theoretical image. Partial truths will emerge, and their mutual intermeshing will gradually raise truth to higher levels. … It has always proven prejudicial to attribute general validity to a partial truth. Yet, a partial truth could not have been reached without overstating its value. Thus the history of truth is intimately interconnected with the history of (...) emotion, but the latter has remained in the dark.Robert Musil, The Man Without Qualities. (shrink)

There is a perennial philosophical dream of a certain natural order for the natural kinds. The name of this dream is ‘the hierarchy requirement’. According to this postulate, proper natural kinds form a taxonomy which is both unique and traditional. Here I demonstrate that complex scientific objects exist: objects which generate different systems of scientific classification, produce myriad legitimate alternatives amongst the nonetheless still natural kinds, and make the hierarchical dream impossible to realize, except at absurdly great cost. Philosophical (...) hopes for a certain order in nature cannot be fulfilled. Natural kinds crosscut one another, ubiquitously so, and this crosscutting spells the end of the hierarchical dream. (shrink)

This paper studies a special scheduling problem under hierarchical management in nurse staff. This is a more complex rostering problem than traditional nurse scheduling. The first is that the rostering requirements of charge nurses and general nurses are different under hierarchical management. The second is that nurses are preferable for relative fair rather than absolute fair under hierarchical management. The model aims at allocating the required workload to meet the operational requirements, weekend rostering preferences, and relative fairness (...) preferences. Two hybrid heuristic algorithms based on multiobjective grey wolf optimizer and three corresponding single heuristic algorithms are employed to solve this problem. The experimental results based on real cases from the Third People’s Hospital, Panzhihua, China, show that MOGWO does not as good as it does on other engineering optimization. However, the hybrid algorithms based on MOGWO are better than corresponding single algorithms on generational distance and spacing of Pareto solutions. Furthermore, for relative fair rostering objective, NSGAII-MOGWO has more power to find the optimal solution in the dimension of relative fairness. (shrink)

Dynamics of complex systems is often hierarchically organized on different time scales. To understand the physics of such hierarchy, here Brownian motion of a particle moving through a fluctuating medium with slowly varying temperature is studied as an analytically tractable example, and a kinetic theory is formulated for describing the states of the particle. What is peculiar here is that the (inverse) temperature is treated as a dynamical variable. Dynamical hierarchy is introduced in conformity with the adiabatic scheme. Then, a (...) new analytical method is developed to show how the Fokker–Planck equation admits as a stationary solution the Maxwellian distribution modulated by the temperature fluctuations, the distribution of which turns out to be determined by the drift term. A careful comment is also made on so-called superstatistics. (shrink)

The network concept is increasingly used for the description of complex systems. Here, we summarize key aspects of the evolvability and robustness of the hierarchical network set of macromolecules, cells, organisms and ecosystems. Listing the costs and benefits of cooperation as a necessary behaviour to build this network hierarchy, we outline the major hypothesis of the paper: the emergence of hierarchical complexity needs cooperation leading to the ageing (i.e. gradual deterioration) of the constituent networks. A stable environment (...) develops cooperation leading to over‐optimization, and forming an ‘always‐old’ network, which accumulates damage, and dies in an apoptosis‐like process. A rapidly changing environment develops competition forming a ‘forever‐young’ network, which may suffer an occasional over‐perturbation exhausting system resources, and causing death in a necrosis‐like process. Giving a number of examples we demonstrate how cooperation evokes the gradual accumulation of damage typical to ageing. Finally, we show how various forms of cooperation and consequent ageing emerge as key elements in all major steps of evolution from the formation of protocells to the establishment of the globalized, modern human society. (shrink)

This paper investigates how social enterprises navigate through the ethical complexity of social change and extends the ethical quandaries faced by social enterprises beyond organisational boundaries. Building on the emerging literature on the ethics of SEs, I conceptualise ethics as an engagement with power relations. I develop theoretical arguments to understand the interaction between ethical predispositions of a SE and the normative structure of the social system in which it operates. I applied this conceptualisation in a hierarchical and (...) heterogeneous rural Indian context to provide insights into the moral ambiguity of ethical decision-making and suggest pathways for ethical actions. Taking a qualitative case study approach, I followed an exemplary SE’s implementation process in India. I observed ethical challenges in designing the implementation process, selecting the beneficiaries and sustaining the programme. I also identified three actions of the SE—the action of recognition, the action of reposition and the action of collaboration—and developed a transformative process model. I discuss the theoretical implications of this research for SEs and recommend a critical engagement with ethical theories to address systemic problems. (shrink)

This chapter explains the notions of information, communication and learning in the context of the complex adaptive systems theory, under the version proposed by M. Gell‐Mann. Within the class of such systems, it focuses attention on complex and self‐organized natural systems as analyzed by H. Atlan. The chapter describes the epistemological context and the formal definition of self‐organization according to H. Atlan, because this definition results from a re‐interpretation of the Shannonian theorem of the noisy channel by applying it to (...) a system organized into several hierarchical levels. It is gradually restore Atlan's construction of the notion of the meaning of information in a hierarchical system, by contrasting the principles of order from noise and organizational noise and by accordingly distinguishing the concepts of complexity and complication. The principle of complexity from noise, which lies at the heart of the concept of self‐organization proposed by H. Atlan. (shrink)

Individuals who disagree that organizational interests legitimately supersede those of the wider society may experience conflict between their personal standards of ethics and those demanded by an employing organization, a conflict that is well documented. An additional question is whether or not individuals capable of complex moral reasoning experience greater conflict than those reasoning at a less developed level. This question was first positioned in a theoretical framework and then investigated using 115 survey responses from a student sample. Correlational analysis (...) and hierarchical regression indicated that individuals scoring high on the Defining Issues Test measure of Kohlberg's stages of moral development experienced significantly greater workplace ethical conflict than low scorers. The finding that complex moral reasoners perceive greater conflict between their personal standards and typical organizational demands raises the issue of what reasoning orientation is rewarded in organizations. Individuals capable of complex moral reasoning may be likely to leave traditional organizations due to high conflict but more ethically friendly organizations for complex reasoners seem unlikely unless these people occupy influential positions. (shrink)

Complexes of two or more proteins form many, if not most, of the intracellular “machines” that execute physical and chemical work, and transmit information. Complexes can form from stochastic post‐translational interactions of fully formed proteins, but recent attention has shifted to co‐translational interactions in which the most common mechanism involves binding of a mature constituent to an incomplete polypeptide emerging from a translating ribosome. Studies in yeast have revealed co‐translational interactions during formation of multiple major complexes, and together with recent (...) mammalian cell studies, suggest widespread utilization of the mechanism. These translation‐dependent interactions can involve a single or multiple mRNA templates, can be uni‐ or bi‐directional, and can use multi‐protein sub‐complexes as a binding component. Here, we discuss benefits of co‐translational complex assembly including accuracy and efficiency, overcoming hidden interfaces, localized and hierarchical assembly, and reduction of orphan protein degradation, toxicity, and dominant‐negative pathogenesis, all serving to improve cell fitness. (shrink)

Evidence can be complex in various ways: e.g., it may exhibit structural complexity, containing information about causal, hierarchical or logical structure as well as empirical data, or it may exhibit combinatorial complexity, containing a complex combination of...

Considering the importance of China’s digital economy, industrial Internet, and high-quality development, this study analyzed China’s urban network from the perspective of the communications technology service industry. Three sub-networks and a comprehensive network were constructed. The density, centrality, and cohesive subgroups of the above network were identified. The results show that: cohesion of urban networks in China is weak and resource sharing is low. From west to east, the urban network forms a multilevel diamond structure in the periphery, a parallelogram (...) structure in the semiperiphery, and a triangle structure in the center. The spatial distribution of cohesive subgroups is scattered, disobeying the first law of geography. By constructing sub-networks and a comprehensive network, the subnetworks that dominate China’s urban networks were identified and their typical characteristics described. This study clarifies the technical support pattern behind China’s digital economy development and industrial internet construction and provides a basis for policy-makers to optimize the country’s high-quality development in the future. (shrink)

Gut microbiome plays a significant role in defining the health status of subjects, and recent studies highlight the importance of using time series strategies to analyse microbiome dynamics. In this paper, we develop a Bayesian model for microbiota longitudinal data, based on Dirichlet distribution with time-varying parameters, that take into account the compositional paradigm and consider principal balances. The proposed model can be effective for predicting the future dynamics of a microbial community in the short term and for analysing the (...) microbial interactions using the value of the estimated parameters. The usefulness of the proposed model is illustrated with six different datasets, and a comparison study with four alternative models is provided. (shrink)

Continues the discussion of theoretical and practical perfection by examining the considerations that give some beliefs and intentions more quality and therefore value than others. It argues that Aristotelian considerations about rationality as essential to humans require measures of quality to be formal, considering only formal properties of beliefs and ends rather than their substantive content. There are two such measures: the extent of a belief's or end's content in space, time, and objects involved, and the degree to which different (...) beliefs and ends are organized in a hierarchical structure. Together, these measures value explanatorily organized knowledge, a unified life, and complex, difficult activities such as games. (shrink)

In this paper I suggest that several problems in the study of emotion depend on a lack of adequate analytical tools, in particular on the tendency of viewing the organism as a modular and hierarchical system whose activity is mainly constituted by strictly sequential causal events. I argue that theories and models based on this view are inadequate to account for the complex reciprocal influences of the many ingredients that constitute emotions. Cognitive processes, feelings and bodily states are so (...) subtly intertwined that it is not possible to determine which one "comes first" in a causal chain. The dynamical systems approach in cognitive science, I suggest, provides a more appropriate framework for the study of emotion. In particular, the notion of circular causation and collective action help depict the organism as a self-organising system in which emotion emerges as a function of its global activity. Among others, this dynamical perspective allows revising the popular notion of appraisal in a way that can dissolve some of the questions that have taunted emotion theorists thus far. (shrink)

Despite hundreds of definitions, no consensus exists on a definition of life or on the closely related and problematic definitions of the organism and death. These problems retard practical and theoretical development in, for example, exobiology, artificial life, biology and evolution. This paper suggests improving this situation by basing definitions on a theory of a generalized particle hierarchy. This theory uses the common denominator of the “operator” for a unified ranking of both particles and organisms, from elementary particles to animals (...) with brains. Accordingly, this ranking is called “the operator hierarchy”. This hierarchy allows life to be defined as: matter with the configuration of an operator, and that possesses a complexity equal to, or even higher than the cellular operator. Living is then synonymous with the dynamics of such operators and the word organism refers to a select group of operators that fit the definition of life. The minimum condition defining an organism is its existence as an operator, construction thus being more essential than metabolism, growth or reproduction. In the operator hierarchy, every organism is associated with a specific closure, for example, the nucleus in eukaryotes. This allows death to be defined as: the state in which an organism has lost its closure following irreversible deterioration of its organization. The generality of the operator hierarchy also offers a context to discuss “life as we do not know it”. The paper ends with testing the definition’s practical value with a range of examples. (shrink)

The approach of the complex network has well described seismic complex systems. In this paper, this is the first time three classical network construction methods for seismicity are compared. By using the same dataset from the Southern California Seismic Network, three networks are constructed. They all present the scale-free, small-world properties, a strength-degree correlation, and an assortative mixing feature. However, they show some differences in the hierarchical clustering feature. On observing the evolution results, three measures show a similar correlation (...) with seismicity dynamics, but one measure shows a different result. These results show that different network construction methods will present some similarities and differences in network properties. This situation needs to be considered, especially when discussing a predictive indicator of seismicity. (shrink)

In this article I suggest a view of evolution characterized as a progressive process toward successively higher levels of complexity. In this approach, complexity is defined by means of an operational definition giving the possibility of its measurement by means of a procedure in which development has a crucial role. Furthermore, the concept of competition applied in the complexity space explains the cumulative emergence of new species as well as the presence of stagnant species. In this process, (...) species are formed in a hierarchical order in which the human species is situated on the highest level. This view of evolution, thus also embracing human cultural evolution, is depicted in a diagram of complexity versus time, thus forming a new kind of a Tree of Life. The purpose of the suggested interpretation of evolution is to make it more readily acceptable for common people. (shrink)

Dienes & Perner present a hierarchical model that addresses the nature – implicit versus explicit – of knowledge in areas as diverse as learning, memory, and visual perception. This framework appears difficult to apply to complex situations, such as those involving implicit learning, because of the indeterminacy that remains regarding knowledge at the low-level in the hierarchy. These reservations should not detract from the positive features of this model. Among its other advantages, it is well adapted to priming phenomena (...) in which the information responsible for the individual's behavior can be precisely defined. (shrink)

The logic of genetic discovery has changed little over time, but the focus of biology is shifting from simple genotype–phenotype relationships to complex metabolic, physiological, developmental, and behavioral traits. In light of this, the traditional reductionist view of individual genes as privileged difference‐making causes of phenotypes is re‐examined. The scope and nature of genetic effects in complex regulatory systems, in which dynamics are driven by regulatory feedback and hierarchical interactions across levels of organization are considered. This review argues that (...) it is appropriate to treat genes as specific actual difference‐makers for the molecular regulation of gene expression. However, they are often neither stable, proportional, nor specific as causes of the overall dynamic behavior of regulatory networks. Dynamical models, properly formulated and validated, provide the tools to probe cause‐and‐effect relationships in complex biological systems, allowing to go beyond the limitations of genetic reductionism to gain an integrative understanding of the causal processes underlying complex phenotypes. (shrink)