Here, for the first time, development studies encounters the set of ideas popularly known as 'Chaos Theory'. Samir Rihani applies to the processes of economic development, ideas from complex adaptive systems like uncertainty, complexity, and unpredictability. Rihani examines various aspects of the development process - including the World Bank, debt, and the struggle against poverty - and demonstrates the limitations of fundamentally linear thinking in an essentially non-linear world.

Consciousness has been the bone of contention for philosophers throughout centuries. Indian philosophy largely adopted lived experience as the starting point for its explorations of consciousness. For this reason, from the very beginning, experience was an integral way of grasping consciousness, whose validity as a tool was considered self-evident. Thus, in Indian philosophy, the question was not to move from the brain to mind but to understand experience of an individual and how such an experience is determined through mental structures (...) (and secondarily, the preoccupation with the brain and its relation to the mind). In contrast, cognitive science (the study of mind and cognition through 1 interdisciplinary methods, with emphasis on computational methods) found its debates soaked in discussion which primarily involved the brain and mind. Experience was not considered a primary source of information and its validity had to be established to consider it a source of information of mind. With the rise of physicalism and realization that mental states are correlative to brain states, the body was virtually neglected from involvement in understanding the mind and the attempts to reduce mind to the brain were rampant. The inability to explain subjective experience of an individual through neuroscientific findings alone has urged philosophers to explore other ways of understanding the ontology of mind. Over the last few years, embodied cognition and enactive approach have brought back the body as a central participant in this debate, providing fertile grounds to explain the relation of brain, body and mind. This paper proposes that we understand the brain as a complex system from which the mind emerges. This emergence is marked by the development of novel property of self-consciousness in human beings. The mind is a process which is embedded throughout the body and thus, the body acts as an actualizing medium for the individual. Thus, the brain is a necessary condition for the mind to be while the mind is embedded throughout the body. The brain and mind are in reciprocal causal relationship with one another, as is the body and environment with one another. In this paper, embodied cognition is understood through principles of Merleau Ponty's idea of embodiment, than through Andy Clark and Francis Varela's alone. (shrink)

Complexity and Postmodernism explores the notion of complexity in the light of contemporary perspectives from philosophy and science. The book integrates insights from complexity and computational theory with the philosophical position of thinkers including Derrida and Lyotard. Paul Cilliers takes a critical stance towards the use of the analytical method as a tool to cope with complexity, and he rejects Searle's superficial contribution to the debate.

The complex systems approach (CSA) to characterizing cognitive function is purported to underlie a conceptual and methodological revolution by its proponents. I examine one central claim from each of the contributed papers and argue that the provided examples do not justify calls for radical change in how we do cognitive science. Instead, I note how currently available approaches in ‘‘standard’’ cognitive science are adequate (or even more appropriate) for understanding the CSA provided examples.

Part I [sections 2–4] draws out the conceptual links between modern conceptions of teleology and their Aristotelian predecessor, briefly outlines the mode of functional analysis employed to explicate teleology, and develops the notion of cybernetic organisation in order to distinguish teleonomic and teleomatic systems. Part II is concerned with arriving at a coherent notion of intentional control. Section 5 argues that intentionality is to be understood in terms of the representational properties of cybernetic systems. Following from this, section 6 argues (...) that intentional control needs to be seen as a particular type of relationship between the system and its environment. (shrink)

Despite the close connection between the central limit theorem and renormalization group (RG) methods, the latter should be considered fundamentally distinct from the kind of probabilistic framework associated with statistical mechanics, especially the notion of averaging. The mathematics of RG is grounded in dynamical systems theory rather than probability, which raises important issues with respect to the way RG generates explanations of physical phenomena. I explore these differences and show why RG methods should be considered not just calculational tools but (...) the basis for a physical understanding of complex systems in terms of structural properties and relations. (shrink)

In _Complexity and Postmodernism_, Paul Cilliers explores the idea of complexity in the light of contemporary perspectives from philosophy and science. Cilliers offers us a unique approach to understanding complexity and computational theory by integrating postmodern theory into his discussion. _Complexity and Postmodernism_ is an exciting and an original book that should be read by anyone interested in gaining a fresh understanding of complexity, postmodernism and connectionism.

The arts are one of the most complex of human endeavours, and so it is fitting that a special issue on Complex Systems in Aesthetics and Arts is being published. As the editors of this special issue, we would like to thank the reviewers of the submitted papers for their hard work in making this issue possible, as well as the authors who submitted their work and were very responsive to the comments of the reviewers and editors.

Ecologist Richard Levins argues population biologists must trade‐off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins's thesis that there is a necessary trade‐off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sober's arguments fail (...) since Levins's thesis concerns the pragmatic features of model building not just the formal properties of models. (shrink)

Complex systems research is becoming ever more important in both the natural and social sciences. It is commonly implied that there is such a thing as a complex system, different examples of which are studied across many disciplines. However, there is no concise definition of a complex system, let alone a definition on which all scientists agree. We review various attempts to characterize a complex system, and consider a core set of features that are widely associated (...) with complex systems in the literature and by those in the field. We argue that some of these features are neither necessary nor sufficient for complexity, and that some of them are too vague or confused to be of any analytical use. In order to bring mathematical rigour to the issue we then review some standard measures of complexity from the scientific literature, and offer a taxonomy for them, before arguing that the one that best captures the qualitative notion of the order produced by complex systems is that of the Statistical Complexity. Finally, we offer our own list of necessary conditions as a characterization of complexity. These conditions are qualitative and may not be jointly sufficient for complexity. We close with some suggestions for future work. (shrink)

Regularities in natural language systems, despite their cognitive advantages in terms of storage and learnability, often coexist with exceptions, raising the question of whether and why irregularities survive. We offer a complex system perspective on this issue, focusing on the irregular past tense forms in English. Two separate processes affect the overall regularity: new verbs constantly entering the vocabulary in the regular form at low frequency, and transitions in both directions occurring in a narrow frequency range. The introduction of (...) new verbs leads to an increase in regular types, that, entering at low frequencies, have a small impact on the perceived irregularity in terms of tokens. The frequency of usage acts as a control parameter, the majority of verbs types being fully-regular at low frequencies, with no evidence of irregularity facing extinction. Very few verbs types in an intermediate frequency region exhibit both regular and irregular forms at the same time, suggesting that the coexistence is unstable. The observed pattern of usage showing an abrupt change in response to small variations of the control parameter only appears in agent-based models provided that the word state is non-binary. By introducing this key ingredient, high-frequency irregular past-tense can survive the tendency to regularize over time, as observed in natural languages. (shrink)

In this article, network science is discussed from a methodological perspective, and two central theses are defended. The first is that network science exploits the very properties that make a system complex. Rather than using idealization techniques to strip those properties away, as is standard practice in other areas of science, network science brings them to the fore, and uses them to furnish new forms of explanation. The second thesis is that network representations are particularly helpful in explaining the (...) properties of non-decomposable systems. Where part-whole decomposition is not possible, network science provides a much-needed alternative method of compressing information about the behavior of complex systems, and does so without succumbing to problems associated with combinatorial explosion. The article concludes with a comparison between the uses of network representation analyzed in the main discussion, and an entirely distinct use of network representation that has recently been discussed in connection with mechanistic modeling. (shrink)

Complex systems are dynamic and may show high levels of variability in both space and time. It is often difficult to decide on what constitutes a given complex system, i.e., where system boundaries should be set, and what amounts to substantial change within the system. We discuss two central themes: the nature of system definitions and their ability to cope with change, and the importance of system definitions for the mental metamodels that we use to describe and order (...) ideas about system change. Systems can only be considered as single study units if they retain their identity. Previous system definitions have largely ignored the need for both spatial and temporal continuity as essential attributes of identity. After considering the philosophical issues surrounding identity and system definitions, we examine their application to modeling studies. We outline a set of five alternative metamodels that capture a range of the basic dynamics of complex systems. Although Holling’s adaptive cycle is a compelling and widely applicable metamodel that fits many complex systems, there are systems that do not necessarily follow the adaptive cycle. We propose that more careful consideration of system definitions and alternative metamodels for complex systems will lead to greater conceptual clarity in the field and, ultimately, to more rigorous research. (shrink)

Ecologist Richard Levins argues population biologists must trade-off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins's thesis that there is a necessary trade-off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sober's arguments fail (...) since Levins's thesis concerns the pragmatic features of model building not just the formal properties of models. (shrink)

"The question of complex systems is relatively new for critics today. Analyzing complex systems in Renaissance texts shows that the Christian kabbalistical concept of harmonia mundi led to an aesthetical development, reflecting the worldview of harmonious parallel worlds. Failure to perceive the esoteric text uniting apparently contradicting themes has often led Renaissance scholars to elaborate a theory of the instability of atmospheres characterizing the English Baroque. This article gives an example of a complex system in Shakespeare's Antony (...) and Cleopatra revealing that the Christian kabbalistical Hercules unifies contradicting metaphors and intertexts of the play, and reintegrates this work in a form of semantic stability more in harmony with the aesthetics of its time. In the case of postmodern literature, contradictory intertexts appear as a device to deconstruct all values and logic previously established. With the study of a text structured by the optical questions around the refraction of light, this paper shows that in the case of Nabokov, the unifying system of apparently contradicting semantic systems is the underlying logic of scientific theory. In Nabokov's text, failing to perceive the fundamental intertext of scientific debate leads one to assimilate Nabokov's writing to a form of postmodern deconstruction. Both cases studied tend to show a continuity of a form of aesthetics through different epistemological eras.". (shrink)

Using the concept of adjunction, for the comprehension of the structure of a complex system, developed in Part I, we introduce the notion of covering systems consisting of partially or locally defined adequately understood objects. This notion incorporates the necessary and sufficient conditions for a sheaf theoretical representation of the informational content included in the structure of a complex system in terms of localization systems. Furthermore, it accommodates a formulation of an invariance property of information communication concerning the (...) analysis of a complex system. (shrink)

Containing selected papers on the fundamentals and applications of Complexity Science, this multi-disciplinary book presents new approaches for resolving complex issues that cannot be resolved using conventional mathematical or software models. Complex Systems problems can occur in a variety of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. Complexity Science problems, the science of open systems consisting of large numbers of diverse components engaged in rich interaction, can occur in (...) a variety of areas such as physical sciences and engineering, the economy, the environment, humanities and social and political sciences. The global behaviour of these systems emerges from the interaction of constituent components and is unpredictable but not random. The key attribute of Complex Systems is the ability to self-organise and adapt to unpredictable changes in their environment. (shrink)

This chapter contains sections titled: Studying the Complexity of Educational Change Developing a Conceptual Framework Lessons for Modeling from Real Cases A Philosophical Note Conclusions References.

So far, the sciences of complexity have received less attention from philosophers than from scientists. Responding to Salthe’s (Found Sci 15, 4(6):357–367, 2010a ) model of evolution, I focus on its metaphysical implications, asking whether the implications of his canonical developmental trajectory (CDT) must be materialistic as his reading proposes.

The standard assumptions that underlie many conceptual and quantitative frameworks do not hold for many complex physical, biological, and social systems. Complex systems science clarifies when and why such assumptions fail and provides alternative frameworks for understanding the properties of complex systems. This review introduces some of the basic principles of complex systems science, including complexity profiles, the tradeoff between efficiency and adaptability, the necessity of matching the complexity of systems to that of their environments, multiscale (...) analysis, and evolutionary processes. Our focus is on the general properties of systems as opposed to the modeling of specific dynamics; rather than provide a comprehensive review, we pedagogically describe a conceptual and analytic approach for understanding and interacting with the complex systems of our world. This paper assumes only a high school mathematical and scientific background so that it may be accessible to academics in all fields, decision-makers in industry, government, and philanthropy, and anyone who is interested in systems and society. (shrink)

In this article we analyze in a new way the epistemological concept of mythical explanation. It is shown, within the framework of the theory of dynamic and complex systems, that this kind of explanation is grounded on the substitution of distributed causation by lineal and single causes. Considering four examples, we show which mechanism is operating in that substitution. The first one concerns a computational implementation of a racial segregation model. The second one will be the analysis of an (...) imaginary panic. The third one starts with the theory, developed by René Girard, concerning sacrifice rituals and the emergence of scapegoats. Finally, the fourth one is based on the introduction of the imitation mechanism as an explanation for the financial markets behavior. (shrink)

Can we understand important social issues by studying individual personalities and decisions? Or are societies somehow more than the people in them? Sociologists have long believed that psychology can't explain what happens when people work together in complex modern societies. In contrast, most psychologists and economists believe that if we have an accurate theory of how individuals make choices and act on them, we can explain pretty much everything about social life. Social Emergence takes a new approach to these (...) longstanding questions. Sawyer argues that societies are complex dynamical systems, and that the best way to resolve these debates is by developing the concept of emergence, focusing on multiple levels of analysis - individuals, interactions, and groups - and with a dynamic focus on how social group phenomena emerge from communication processes among individual members. This book makes a unique contribution not only to complex systems research but also to social theory. (shrink)

Some theorists who emphasize the complexity of biological and cognitive systems and who advocate the employment of the tools of dynamical systems theory in explaining them construe complexity and reduction as exclusive alternatives. This paper argues that reduction, an approach to explanation that decomposes complex activities and localizes the components within the complex system, is not only compatible with an emphasis on complexity, but provides the foundation for dynamical analysis. Explanation via decomposition and localization is nonetheless extremely challenging, (...) and an analysis of recent cognitive neuroscience research on memory is used to illustrate what is involved. Memory researchers split between advocating memory systems and advocating memory processes, and I argue that it is the latter approach that provides the critical sort of decomposition and localization for explaining memory. The challenges of linking distinguishable functions with brain processes is illustrated by two examples: competing hypotheses about the contribution of the hippocampus and competing attempts to link areas in frontal cortex with memory processing. (shrink)

A key topic in the work of Burghard Rieger is the notion of meaning. To explore this notion, he and his collaborators developed a most sophisticated approach combining theoretical ideas and concepts of semiotics with empirical and numerical tools of computational linguistics. In the present contribution, relations of Rieger’s achievements to some issues of interest in the physics and philosophy of complex systems will be addressed.

We develop a category theoretical scheme for the comprehension of the information structure associated with a complex system, in terms of families of partial or local information carriers. The scheme is based on the existence of a categorical adjunction, that provides a theoretical platform for the descriptive analysis of the complex system as a process of functorial information communication.

Nowadays, the development of big data is getting faster and faster, and the related research on motion sensing recognition and complex systems under the background of big data is gradually being valued. At present, there are relatively few related researches on vertical Baduanjin in the academic circles; research in this direction can make further breakthroughs in motion sensor recognition. In order to carry out related action recognition research on the lifting action of vertical Baduanjin, this paper uses sensor technology (...) to collect the motion video image of vertical Baduanjin based on the background of big data and uses action recognition technology and related algorithms to obtain the action. Recognize the video image to obtain the data, get the acceleration, angular velocity, and EMG data, and count the end time and duration according to the change of the action. According to the data table and graph change trend compiled at the end of the experiment, we can see the following: after the data is preprocessed, the acceleration signal change range is limited to [−1, 1], and the acceleration change has a clear directionality; and, after 15 lifts of the detected object, its angular velocity in X-axis direction is basically negative. However, when the ninth lift is performed, the angular velocity of the movement in X-axis direction is 36.09, the largest of all angular velocities. When performing the 15th lifting action, the angular velocity of this action in Z-axis direction is −26.05, which is the smallest of all angular velocities. The longest duration of the left muscle discharge during the lifting action of the subject is 15.24 for the tibial anterior muscle and 8.91 for the external oblique muscle with the shortest duration. The longest discharge duration of the right muscle is also the tibial anterior muscle with 12.15, and the shortest duration is the erector spinae with 8.79. (shrink)

Traditional modes of system representation as dynamical systems, involving fixed sets of states together with imposed dynamical laws, pertain only to a meagre subclass of natural systems. This reductionistic paradigm leaves no room for final causes; constrained thus are the simple systems. Members of their complementary collection, natural systems having mathematical models that are not dynamical systems, are the complex systems. Complex systems, containing hierarchical cycles in their entailment networks, can only be approximated and simulated, locally and temporarily, (...) by simple ones. Anticipatory systems are, in this specific sense, complex, hence this introductory chapter on Complex Systems in the Handbook of Anticipation. (shrink)

How might we usefully apply concepts and procedures derived from the study of other complex dynamical systems to analyzing systemic change in education? In this article we begin to define possible agendas for research toward developing systematic frameworks and shared terminology for such a project. We illustrate the plausibility of defining such frameworks and raise the question of the relation between such frameworks and the crucial task of aggregating data across ‘systemic experiments’, such as those conducted under the Urban (...) Systemic Initiative sponsored by the US National Science Foundation. Our discussion includes a review of key issues identified by groups of researchers regarding Defining the System, Structural Analysis, Relationships Among Subsystems and Levels, Drivers for Change, and Modeling Methods. (shrink)

I argue for an inferentialist account of the meaning of causal claims, which draws on the writings of Sellars and Brandom. The account is meant to be widely applicable. In this work, it is motivated and defended with reference to complex systems sciences, i.e., sciences that study the behaviour of systems with many components interacting at various levels of organisation (e.g. cells, brain, social groups). Here are three, seemingly-uncontroversial platitudes about causality. (1) Causal relations are objective, mind-independent relations and, (...) as such, analysable in objective, mind-independent terms. (2) There is a tight connection between our practice of predicting, explaining and controlling phenomena, and the use of causal notions. (3) The second platitude should be explained in terms of the first. Contrary to this widely-held stance, I suggest that we reverse the order of analysis, by taking our activities of agents as the raw material in terms of which to account for the obtaining of causal relations. To this end, I propose and defend an inferentialist account of causality. Causality is a ‘category’ that the knowing subject employs to ‘mediate’ between himself and the world. In inferentialist terms, this mediation is the result of the concept of cause figuring in a network of inferences, used in our practice of gathering evidence and using it to explain, predict and intervene. Complexity only makes the mediation more difficult, thereby rendering the meaning of causality more evident. (shrink)

The relationship between brain and mind has been extensively explored through the developments within neuroscience over the last decade. However, the ontological status of mind has remained fairly problematic due to the inability to explain all features of the mind through the brain. This inability has been considered largely due to partial knowledge of the brain. It is claimed that once we gain complete knowledge of the brain, all features of the mind would be explained adequately. However, a challenge to (...) such a position is downward causation: How do we explain the causal power that mental states exert over brain activities? If we agree that downward causation occurs, then to what extent could a sole explanation of brain activities account for our behaviour? (For they would in themselves be conditioned by the mental states which are left unexplained). This dissertation is an attempt to understand relation between brain and mind through the concept of emergence, placed in the context of complex systems approach. This will create a space to account for the causal power of mental states. The complex systems approach says that as the complexity of a system increases, we witness the emergence of novel qualities and after a certain threshold (of complexity), the emergence of a novel structure. When the body (and correspondingly, brain) reaches a certain level of complexity, the mind emerges. The brain is a complex system from which the mind emerges. The brain, consisting of billions of neurons interacting with each other, regulates the body placed in the environment. The interaction of neurons (local interactions involving self-organization) result in dynamical brain signatures (global synergy). Such signatures are correlative to mental states. Mind is the process of a living organism embodying an intentional stance. This object could be the subject itself or another distinct from the subject. With the emergence of mind, the causal powers of brain are conditioned by the mind. Such a conditioning is evident through the causal efficacy of mental states. While the brain is minimal condition for the mind to emerge, the mind in itself is embedded (showcased/explicated/manifested) throughout the body. The mind is a process that belongs to body-as-a-whole with the novel quality of intentionality. A preliminary to understanding this relation is its metaphysical inclination. A large portion of the history of philosophy of mind has advocated a metaphysics of entities where the mind and body have been seen as two entities with distinct essences. However, such attribution of entity-ship does not take into account the processual nature of these existents (that they are essentially dependent on their environment for their existence and sustenance). Thus, the category of processual unity has been introduced which sought to account for existent as emergent wholes that move towards a stable equilibrium through self-organization. By considering existents to be processual unities, we can account for their identity as a whole-in-itself (what has been called organizational closure) and also for their processual nature. The brain is a component of the body which is a complex system and is representative of the body’s stance in the world. The brain, consisting of billions of neurons interacting with each other, regulates the body placed in the environment. The interaction of neurons (local interactions involving self-organization) result in dynamical brain signatures (global synergy). Such signatures are correlative to mental states. These mental states in turn condition the brain patterns, that allows the embodying of mental states. Thus, the three-way process of the representation of body in the world by the brain, the emergence of mental state through dynamic brain patterns and the reciprocal causal power on the brain patterns by the mental states marks embodiment. The relation between brain, body and mind can be outlined as follows: A. There are complex interactions in the brain. These interactions are representative of the body’s stance in the world and are present in form of dynamical brain signatures. B. The dynamical brain signatures lead to emergence of mind as a process. The mental state has causal power which conditions the brain. C. The brain conditioned by causal power of the mind carries out embodiment of the mind throughout the body. In the dissertation, an exposition on relation between brain and mind through complex system approach is followed by a brief on relation between body and mind. The radical embodiment approach adopts the nonlinear dynamic systems theory to understand relation of brain, body and mind. It states a shift from mapping of cognitive states onto Neural Correlates of Consciousness to their mapping through dynamic brain signatures. Every mental state is embedded throughout the body. The dissertation explores the three features of consciousness, intentionality and qualia. These have previously formed a challenge within a dualistic framework and the dissertation intends to show a direction in which they can be accounted for, within the complex systems approach and radical embodiment viewpoint. After a certain threshold of the rate of production of cell assemblies is bypassed, we become conscious of the representation itself. This leads to emergence of phenomenal states. Qualia is the qualitative character of such states, which belong to the body-as-a-whole and for this reason, cannot be reduced to properties of any of the components from which it emerges (the dynamic brain signatures) or in which it is embodied (the body and its individual parts) alone. Intentionality is the novel property of mind of moving towards a certain set of attractors where attractors refer to the states that the system prefers (which would positively contribute to its fitness). The scope of this dissertation is to delineate the relation of brain to the mind and unravel some persistent troubles of philosophy of mind within such delineation. The types of components and their relation within the mind preceded by a thorough study of how the mind is embodied is an area yet to be extensively explored in the coming works. (shrink)

How might we usefully apply concepts and procedures derived from the study of other complex dynamical systems to analyzing systemic change in education? In this article we begin to define possible agendas for research toward developing systematic frameworks and shared terminology for such a project. We illustrate the plausibility of defining such frameworks and raise the question of the relation between such frameworks and the crucial task of aggregating data across ‘systemic experiments’, such as those conducted under the Urban (...) Systemic Initiative sponsored by the US National Science Foundation. Our discussion includes a review of key issues identified by groups of researchers regarding (1) Defining the System, (2) Structural Analysis, (3) Relationships Among Subsystems and Levels, (4) Drivers for Change, and (5) Modeling Methods. (shrink)

For a long time, linguists more or less denied the existence of individual differences in grammatical knowledge. While recent years have seen an explosion of research on individual differences, most usage-based research has failed to address this issue and has remained reluctant to study the synergy between individual and community grammars. This paper focuses on individual differences in linguistic knowledge and processing, and examines how these differences can be integrated into a more comprehensive constructionist theory of grammar. The examination is (...) guided by the various challenges and opportunities that may be extracted from scattered research that exists across disciplines touching on these matters, while also presenting some new data that illustrate how differentiation between individuals can improve models of long-term language change. The paper also serves as the introduction to this special issue of Cognitive Linguistics, which collects seven contributions from various linguistic disciplines focusing on key aspects of individuals’ grammars. (shrink)

Systems architecture and its associated parallel biology generate architectural forms that are both green and surreal by nature. The connection between systems architecture and Leo Lionni's fantastic book Parallel Botany are considered as architects are now starting to have the ability to create great works of biological parallelism using technologies that are highly sur real, they are on top of the real.

Willard van Orman Quine once said that he had a preference for a desert ontology. This was in an earlier day when concerns with logical structure and ontological simplicity reigned supreme. Ontological genocide was practiced upon whole classes of upper-level or ‘derivative’ entities in the name of elegance, and we were secure in the belief that one strayed irremediably into the realm of conceptual confusion and possible error the further one got from ontic fundamentalism. In those days, one paid more (...) attention to generic worries about possible errors than to actual errors derived from distancing oneself too far from the nitty-gritty details of actual theory, actual inferences from actual data, the actual conditions under which we posited and detected entities, calibrated and ‘burned in’ instruments, identified and rejected artifacts, debugged programs and procedures, explained the mechanisms behind regularities, judged correlations to be spurious, and in general, to the real complexities and richness of actual scientific practice. (shrink)

In the last 20 years, a stream of research emerged under the label of „complex problem solving“ (CPS). This research was intended to describe the way people deal with complex, dynamic, and intransparent situations. Complex computer-simulated scenarios were as stimulus material in psychological experiments. This line of research lead to subtle insights into the way how people deal with complexity and uncertainty. Besides these knowledge-rich, realistic, intransparent, complex, dynamic scenarios with many variables, a second line of (...) research used more simple, knowledge-lean scenarios with a low number of variables („minimal complex systems“, MCS) that have been proposed recently in problem-solving research for the purpose of educational assessment. In both cases, the idea behind the use of microworlds is to increase validity of problem solving tasks by presenting interactive environments that can be explored and controlled by participants while pursuing certain action goals. The main argument presented here is: both types of systems - CPS and MCS – can only be dealt with successfully if causal dependencies between input and output variables are identified and used for system control. System knowledge is necessary for control and intervention. But CPS and MCS differ in their way of how causal dependencies are identified and how the mental model is constructed; therefore, they cannot be compared directly to each other with respect to the cognitive processes that are necessary for solving the tasks. Knowledge-poor MCS tasks address only a small fraction of the cognitive processes and structures needed for knowledge-rich CPS situations. (shrink)