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Researchers of advanced technologies are constantly seeking new ways of measuring and adapting to user performance. Appropriately adapting system feedback requires accurate assessments of user performance. Unfortunately, many assessment algorithms must be trained on and use pre‐prepared data sets or corpora to provide a sufficiently accurate portrayal of user knowledge and behavior. However, if the targeted content of the tutoring system changes depending on the situation, the assessment algorithms must be sufficiently independent to apply to untrained content. Such is the (...) case for Interactive Strategy Training for Active Reading and Thinking (iSTART), an intelligent tutoring system that assesses thecognitivecomplexity of strategy use while a reader self‐explains a text. iSTART is designed so that teachers and researchers may add their own (new) texts into the system. The current paper explores student self‐explanations from newly added texts (which iSTART had not been trained on) and focuses on evaluating the iSTART assessment algorithm by comparing it to human ratings of the students’ self‐explanations. (shrink)

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Some ideologies, such as liberalism, conservatism, and socialism, are complex symbolic structures. Mastering them requires specialization, and because we are all amateurs in almost all symbolically rich domains, most people are not ideologically sophisticated. Instead, they reason about politics in a maturationally natural way, via friend-foe representations and inferences based on those representations (for example, friends of foes are foes). However, even complex ideologies are much simpler than the political, economic, and social systems that they are supposed to represent. Hence, (...) all ideologies are inaccurate to varying degrees. More subtly, all are incomplete in various ways; in particular, they fail to anticipate some crucial events (for example, global warming), which leads to unanticipated value trade-offs and strategic conundrums. Ideologists sometimes adapt to incompleteness via recombinant innovation, producing hybrid ideologies (for example, ecosocialism). In turn, this tends to produce inconsistencies between new and old parts of an ideology. Thus, inaccuracy, incompleteness, and inconsistency are not pathologies of political belief systems. They are the inevitable result of ideologists grappling with a reality that is far more complex than their symbolic constructions can be. Therefore, evaluations of ideologies that identify errors, incompleteness, or inconsistency at a single point in time are often unenlightening. Following Imre Lakatos, evaluations should focus on how a sequence of ideologies—an ideological tradition—evolves. (shrink)

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The confusion/non-consequential thinking explanation proposed by Newstead, Girotto, and Legrenzi (1995) for poor performance on Wason's THOG problem (a hypothetico-deductive reasoning task) was examined in three experiments with 300 participants. In general, as thecognitivecomplexity of the problem and the possibility of non-consequential thinking were reduced, correct performance increased. Significant but weak facilitation (33-40% correct) was found in Experiment 1 for THOG classification instructions that did not include the indeterminate response option. Substantial facilitation (up to 75% correct) (...) was obtained in Experiment 2 with O'Brien et al.'s (1990) one-other-THOG classification instruction. In Experiment 3, a revised version of O'Brien et al.'s pre-test problem format also led to substantial facilitation, even with the use of the standard three-choice THOG classification instruction. These findings are discussed in terms of Newstead et al.'s theoretical proposal and possible attentional factors. (shrink)

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An application of the Method of Analysis of RelationalComplexity (MARC) to suppositional reasoning in the knight-knave task is outlined. The task requires testing suppositions derived from statements made by individuals who either always tell the truth or always lie. Relationalcomplexity (RC) is defined as the number of unique entities that need to be processed in parallel to arrive at a solution. A selection of five ternary and five quaternary items were presented to 53 psychology students using (...) a pencil and paper format. A computer-administered version was presented to 50 students. As predicted, quaternary problems were associated with higher error rates and longer response times than ternary problems. The computer-administered form was more difficult than the pencil and paper version of the test. These differences are discussed in terms of RC theory and alternative processing accounts. Together, they indicate that the relationalcomplexity metric is a useful and parsimonious way to quantifycomplexity of reasoning tasks. (shrink)

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The arbitrariness of a signal has long been seen as a theoretically important but difficult to pin down notion. In this article, we suggest there are at least two different notions of arbitrariness at play in philosophical and scientific debates concerning the use of arbitrary signals, and work towards improved analyses of both. We then consider how these different types of arbitrariness can co-occur and come apart. Finally, we examine the connections between these two types of arbitrariness and the (...) class='Hi'>cognitivecomplexity of signal users with an eye towards better evaluating one possible form of human-nonhuman communicative continuity. We show that each type of arbitrariness bears its own nuanced relationship tocognitivecomplexity, demonstrating the theoretical importance of keeping these two notions separate. (shrink)

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What is the relation between perceptual experience and the suite of sensorimotor skills that enable us to act in the very world we perceive? The relation, according to ‘sensorimotor models’ is tight indeed. Perceptual experience, on these accounts, is enacted via skilled sensorimotor activity, and gains its content and character courtesy of our knowledge of the relations between movement and sensory stimulation. I shall argue that this formulation is too extreme, and that it fails to accommodate the substantial firewalls, dis-integrations, (...) and specialpurpose streamings that form the massed strata of human cognition. In particular, such strong sensorimotor models threaten to obscure the computationally potent insensitivity of key information-processing events to the full subtleties of embodied cycles of sensing and moving. (shrink)

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(2013). Why humans are (sometimes) less rational than other animals:Cognitivecomplexity and the axioms of rational choice. Thinking & Reasoning: Vol. 19, No. 1, pp. 1-26. doi: 10.1080/13546783.2012.713178.

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[Andy Clark] What is the relation between perceptual experience and the suite of sensorimotor skills that enable us to act in the very world we perceive? The relation, according to 'sensorimotor models' (O'Regan and Noë 2001, Noë 2004) is tight indeed. Perceptual experience, on these accounts, is enacted via skilled sensorimotor activity, and gains its content and character courtesy of our knowledge of the relations between (typically) movement and sensory stimulation. I shall argue that this formulation is too extreme, and (...) that it fails to accommodate the substantial firewalls, dis-integrations, and special-purpose streamings that form the massed strata of human cognition. In particular, such strong sensorimotor models threaten to obscure the computationally potent insensitivity of key information-processing events to the full subtleties of embodied cycles of sensing and moving. /// [Naomi Eilan] The strong sensorimotor account of perception gives self-induced movements two constitutive roles in explaining visual consciousness. The first says that self-induced movements are vehicles of visual awareness, and for this reason consciousness 'does not happen in the brain only'. The second says that the phenomenal nature of visual experiences is consists in the action-directing content of vision. In response I suggest, first, that the sense in which visual awareness is active should be explained by appeal to the role of attention in visual consciousness, rather than self-induced movements; and second, that the sense in which perceptual consciousness does not happen in the brain only should be explained by appeal to the relational nature of perceptual consciousness, appeal to which also shows why links with action cannot exhaust phenomenal content. (shrink)

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Behavioural flexibility is often treated as the gold standard of evidence for more sophisticated or complex forms of animal cognition, such as planning, metacognition and mindreading. However, the evidential link between behavioural flexibility and complex cognition has not been explicitly or systematically defended. Such a defence is particularly pressing because observed flexible behaviours can frequently be explained by putatively simplercognitive mechanisms. This leaves complex cognition hypotheses open to ‘deflationary’ challenges that are accorded greater evidential weight precisely because they (...) offer putatively simpler explanations of equal explanatory power. This paper challenges the blanket preference for simpler explanations, and shows that once this preference is dispensed with, and the full spectrum of evidence—including evolutionary, ecological and phylogenetic data—is accorded its proper weight, an argument in support of the prevailing assumption that behavioural flexibility can serve as evidence for complexcognitive mechanisms may begin to take shape. An adaptive model ofcognitive-behavioural evolution is proposed, according to which the existence of convergent trait–environment clusters in phylogenetically disparate lineages may serve as evidence for the same trait–environment clusters in other lineages. This, in turn, could permit inferences ofcognitivecomplexity in cases of experimental underdetermination, thereby placing the common view that behavioural flexibility can serve as evidence for complex cognition on firmer grounds. (shrink)

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In this longitudinal study, we explore the co-evolution of thecognitivecomplexity of the CEO of Puma, Jochen Zeitz, and his view and initiatives on sustainability. Our purpose was to explore how the changes in a leader’s mindset relate to his/her views and actions on sustainability. In contrast to previous studies, we adopt an in-depth longitudinal case study approach to capture the role of leaders’cognitivecomplexity in the context of corporate sustainability. By understanding the (...) class='Hi'>cognitive development of Zeitz as leader of Puma, we provide an important step toward understanding the co-evolution of leaders’cognitivecomplexity and proactive corporate sustainability initiatives over time. Our findings show that as he developed a more complex mindset that also included non-business lenses, Zeitz developed a more inclusive understanding of sustainability and adopted proactive initiatives that went beyond business-as-usual. Our study also demonstrates that a longitudinal perspective can offer valuable insights for a better understanding of how individuals and their interactions affect and are affected by an organization’s strategies and performance, in corporate sustainability and beyond. (shrink)

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The present article constitutes an attempt at a review of a few selected questions related to thecomplexity paradigm and its implications for research on cognition, especially within the so-called ecological approach framework. I propose several theses, among others concerning the two contrary tendencies within the dominant methodology (the propensity to search for simplicity and the growing emphasis on recognizingcomplexity), as well as the ontological consequences of the phenomenon under discussion (ontological emergence and processual emergentism).

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I present evidence for a systematiccomplexity-coherence tradeoff in cognition. I show how feasible strategies for increasingcognitivecomplexity along three dimensions come at the expense of a heightened vulnerability to incoherence. I discuss two normative implications of thecomplexity-coherence tradeoff: a novel challenge to coherence-based theories of bounded rationality and a new strategy for vindicating the rationality of seemingly irrational cognitions. I also discuss how thecomplexity-coherence tradeoff sharpens recent descriptive challenges to dual process (...) theories of cognition. (shrink)

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Unlike birds and mammals, reptiles are commonly thought to possess only the most rudimentary means of interacting with their environments, reflexively responding to sensory information to the near exclusion of highercognitive function. However, reptilian brains, though structurally somewhat different from those of mammals and birds, use many of the same cellular and molecular processes to support complex behaviors in homologous brain regions. Here, the neurological mechanisms supporting reptilian cognition are reviewed, focusing specifically on spatial cognition and the hippocampus. (...) These processes are compared to those seen in mammals and birds within an ecologically and evolutionarily relevant context. By viewing reptilian cognition through an integrative framework, a more robust understanding of reptile cognition is gleaned. Doing so yields a broader view of the evolutionarily conserved molecular and cellular mechanisms that underliecognitive function and a better understanding of the factors that led to the evolution of complex cognition. (shrink)

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The complex systems approach tocognitive science invites a new understanding of extendedcognitive systems. According to this understanding, extendedcognitive systems are heterogenous, composed of brain, body, and niche, non-linearly coupled to one another. This view ofcognitive systems, as non-linearly coupled brain–body–niche systems, promises conceptual and methodological advances. In this article we focus on two of these. First, the fundamental interdependence among brain, body, and niche makes it possible to explain extended cognition without invoking (...) representations or computation. Second, cognition and conscious experience can be understood as a single phenomenon, eliminating fruitless philosophical discussion of qualia and the so-called hard problem of consciousness. What we call “extended phenomenological-cognitive systems” are relational and dynamical entities, with interactions among heterogeneous parts at multiple spatial and temporal scales. (shrink)

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Intractability is a growing concern across thecognitive sciences: while many models of cognition can describe and predict human behavior in the lab, it remains unclear how these models can scale to situations of real-worldcomplexity. Cognition and Intractability is the first book to provide an accessible introduction to computationalcomplexity analysis and its application to questions of intractability incognitive science. Covering both classical and parameterizedcomplexity analysis, it introduces the mathematical concepts and proof (...) techniques that can be used to test one's intuition of tractability. It also describes how these tools can be applied tocognitive modeling to deal with intractability, and its ramifications, in a systematic way. Aimed at students and researchers in philosophy,cognitive neuroscience, psychology, artificial intelligence, and linguistics who want to build a firm understanding of intractability and its implications in their modeling work, it is an ideal resource for teaching or self-study. (shrink)

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This paper investigates the intersection ofcognitive sciences and social network theory and its counterpart, thecomplexity sciences, aiming to shed light on the compatibility and potential integration of these frameworks into institutional theory. Institutional scholars have for long selectively adopted notions linked with thecognitive sciences andcomplexity sciences, such as the notion of path dependence, without exploring the broader implications of systematically integrating such perspectives into institutionalism. This paper aims to advance such a comprehensive (...) theoretical integration, by investigating the effective combination of these approaches and their significant implications. It shows how thecomplexity sciences contribute to dissolving the barriers between thecognitive and social realms and illustrates how this impacts notions of human agency and reflexivity. Theoretical integration also involves acknowledging considerable diversity in individual human agency, which in turn prompts a reconsideration of how notions of institutional stability, change, diffusion and adaptation are understood. Furthermore, the paper addresses the epistemological challenge presented by thecomplexity sciences, before it highlights the general relevance of institutional theory in analyzing complex social phenomena. Finally, the paper explores implications for research methodology, proposing that a fusion of institutional theory and thecomplexity sciences provides a metatheoretical framework for assessing the contextual suitability of different theoretical and methodological approaches. (shrink)

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Children with complex medical conditions including those with severe intellectual disability are living longer. For some, support with medical technology such as Long-Term Ventilation can prolong their lives further. Such technological supports can have significant implications for the child and her family and consume considerable resources though they can also offer real benefits. Sometimes clinicians question whether children with very severecognitive impairments should have their life prolonged by technology, though they would be prepared to provide the same treatment (...) in equivalent cases withoutcognitive disability. We describe and analyse four ways in which this view might be justified. Although it could be claimed that children with severecognitive disability have lives that are not worth living, in most cases this view can and should be rejected. However, the burdens of life-prolonging technology may outweigh the benefits of such treatment either in the present or in the future. Consequently it might not be in their interests to provide such technology, or to ensure that it is provided as part of a time-limited trial. We also consider circumstances where medical technology could offer modest benefits to an individual, but resources are scarce. In the face of resource imitation, treatment may be prioritised to children who stand to benefit the most. This may in some circumstances, justify selectively withholding treatment from some medically complex children. (shrink)

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Following Marr’s famous three-level distinction between explanations incognitive science, it is often accepted that focus on modelingcognitive tasks should be on the computational level rather than the algorithmic level. When it comes to mathematical problem solving, this approach suggests that thecomplexity of the task of solving a problem can be characterized by the computationalcomplexity of that problem. In this paper, I argue that human cognizers use heuristic and didactic tools and thus engage (...) incognitive processes that make their problem solving algorithms computationally suboptimal, in contrast with the optimal algorithms studied in the computational approach. Therefore, in order to accurately model the humancognitive tasks involved in mathematical problem solving, we need to expand our methodology to also include aspects relevant to the algorithmic level. This allows us to study algorithms that are cognitively optimal for human problem solvers. Since problem solving methods are not universal, I propose that they should be studied in the framework of enculturation, which can explain the expected cultural variance in the humanly optimal algorithms. While mathematical problem solving is used as the case study, the considerations in this paper concern modeling ofcognitive tasks in general. (shrink)

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In this commentary, we propose that the shifts in symmetry Wynn documents may be explained in terms of simpler mechanisms than he suggests. Furthermore, we argue that it is dangerous to draw definitive conclusions about thecognitive abilities of a species from the level of symmetry observed in the artefacts produced by that species.

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Complexity science is an investigative framework that stems from a number of tried and tested disciplines—including systems theory, nonlinear dynamical systems theory, and synergetics—and extends a common set of concepts, methods, and principles to understand how natural systems operate. By quantitatively employing concepts, such as emergence, nonlinearity, and self‐organization,complexity science offers a way to understand the structures and operations of naturalcognitive systems in a manner that is conceptually compelling and mathematically rigorous. Thus,complexity science (...) both transforms understandings of cognition and reframes more traditional approaches. Consequently, ifcognitive systems are indeed complex systems, thencognitive science ought to considercomplexity science as a centerpiece of the discipline. (shrink)

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Modern integrative systems biology defines itself by thecomplexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on humancognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other (...) tools to handle thecognitivecomplexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations. (shrink)

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In computationalcomplexity theory, decision problems are divided intocomplexity classes based on the amount of computational resources it takes for algorithms to solve them. In theoretical computer science, it is commonly accepted that only functions for solving problems in thecomplexity class P, solvable by a deterministic Turing machine in polynomial time, are considered to be tractable. Incognitive science and philosophy, this tractability result has been used to argue that only functions in P can (...) feasibly work as computational models of humancognitive capacities. One interesting area of computationalcomplexity theory is descriptivecomplexity, which connects the expressive strength of systems of logic with the computationalcomplexity classes. In descriptivecomplexity theory, it is established that only first-order (classical) systems are connected to P, or one of its subclasses. Consequently, second-order systems of logic are considered to be computationally intractable, and may therefore seem to be unfit to model humancognitive capacities. This would be problematic when we think of the role of logic as the foundations of mathematics. In order to express many important mathematical concepts and systematically prove theorems involving them, we need to have a system of logic stronger than classical first-order logic. But if such a system is considered to be intractable, it means that the logical foundation of mathematics can be prohibitively complex for human cognition. In this paper I will argue, however, that this problem is the result of an unjustified direct use of computationalcomplexity classes incognitive modelling. Placing my account in the recent literature on the topic, I argue that the problem can be solved by considering computationalcomplexity for humanly relevant problem solving algorithms and input sizes. (shrink)

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Impaired neurodevelopmental outcome, in particularcognitive impairment, after neonatal hypoxic-ischemic encephalopathy is a major concern for parents, clinicians, and society. This study aims to investigate the potential benefits of using advanced quantitative electroencephalography analysis for early prediction ofcognitive outcomes, assessed here at 2 years of age. EEG data were recorded within the first week after birth from a cohort of twenty infants with neonatal hypoxic-ischemic encephalopathy. A proposed regression framework was based on two different sets of features, (...) namely graph-theoretical features derived from the weighted phase-lag index and entropies metrics represented by sample entropy, permutation entropy, and spectral entropy. Both sets of features were calculated within the noise-assisted multivariate empirical mode decomposition domain. Correlation analysis showed a significant association in the delta band between the proposed features, graph attributes and entropy features from the neonatal EEG data and thecognitive development at age two years. These features were used to train and test the tree ensemble regression models. The highest prediction performance was reached to 14.27 root mean square error, 12.07 mean absolute error, and 0.45 R-squared using the entropy features with a boosted tree regression model. Thus, the results demonstrate that the proposed qEEG features show the state of brain function at an early stage; hence, they could serve as predictive biomarkers of latercognitive impairment, which could facilitate identifying those who might benefit from early targeted intervention. (shrink)

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Mechanistic frameworks of investigation and explanation dominate thecognitive, neural, and psychological sciences. In this dissertation, I argue that mechanistic frameworks cannot, in principle, explain some kinds of cognition. In its place, I argue thatcomplexity science has methods and theories more appropriate for investigating and explaining somecognitive phenomena. -/- I begin with an examination of the term 'cognition.' I defend the idea that "cognition" has been a moving target of investigation in the relevant sciences. As (...) such it is not historically true that there has been a thoroughly entrenched and agreed upon conception of "cognition." Next, I take up mechanistic frameworks. Although 'mechanism' is an umbrella term for a set of loosely related characteristics, there are common features: linearity, localization, and component dominance. I then describecomplexity science, with emphasis on its utilization of dynamical systems modeling. Next, I discuss two phenomena that typically fall under the purview ofcomplexity science: nonlinearity and interaction dominance. -/- Acomplexity science framework guided by the theory of self-organized criticality and utilizing the methods of dynamical systems modeling can surmount a number of challenges that face mechanistic frameworks when investigating some kinds of cognition. The first challenge is epistemic and concerns the inadequacy of mechanistic frameworks to facilitate the comprehensibility of massive amounts of data across various scales and areas of inquiry. I argue thatcomplexity science is more appropriate for making big data comprehensible when investigating cognition, particularly across disciplines. I demonstrate this via an approach called nested dynamical modeling (NDM). NDM can facilitate comprehensibility of large amounts of data obtained from various scales of investigation by eliminating irrelevant degrees of freedom of that system as relates to the target of investigation. -/- The second shortcoming concerns ontological blind spots within mechanistic frameworks.Cognitive phenomena like extended cognition often fail to meet most, if not all, of the criteria assumed by many mechanistic approaches, especially component dominance. I argue that research guided by the notion of interaction dominance allows for extended cognition to be a real, empirically supported phenomenon within complex systems frameworks. In this chapter I discuss some of my experimental work on extendedcognitive systems. -/- The search for mechanisms can be a reasonable starting position when attempting to explain natural phenomena in the life sciences. However, too strict of an adherence to theoretical and methodological commitments such as linearity, localization, and component dominance can result in intractable epistemic challenges and ontological blind spots.Complexity science has theories and methods to overcome such challenges in the investigation of cognition. (shrink)

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Complex problem solving (CPS) emerged in the last 30 years in Europe as a new part of the psychology of thinking and problem solving. This paper introduces into the field and provides a personal view. Also, related concepts like macrocognition or operative intelligence will be explained in this context. Two examples for the assessment of CPS, Tailorshop and MicroDYN, are presented to illustrate the concept by means of their measurement devices. Also, the relation of complex cognition and emotion in the (...) CPS context is discussed. The question if CPS requires complex cognition is answered with a tentative “yes.”. (shrink)

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Throughout most of the 20th century, analytical and reductionist approaches have dominated in biological, social, and humanistic sciences, including linguistics and communication. We generally believed we could account for fundamental phenomena in invoking basic elemental units. Although the amount of knowledge generated was certainly impressive, we have also seen limitations of this approach. Discovering the sound formants of human languages, for example, has allowed us to know vital aspects of the ‘material’ plane of verbal codes, but it tells us little (...) about significant aspects of their social functions. I firmly believe, therefore, that alongside a linguistics that looks ‘inward’ there should also be a linguistics that looks ‘outward’, or one even that is constructed ‘from the outside’, a linguistics that I refer to elsewhere as ‘holistic’ though it could be identified by a different name. My current vision is to promote simultaneously the perspective that goes from the part to the whole and that which goes from the whole to the parts, i.e., both from the top down and from the bottom up. This goal is shared with other disciplines which recognize that many phenomena related to life are interwoven, self-organising, emergent and processual. Thus, we need to re-examine how we have conceived of reality, both the way we have looked at it and the images we have used to talk about it. Several approaches now grouped under the label ofcomplexity have been elaborated towards this objective of finding new concepts and ways of thinking that better fit the complex organisation of facts and events. (shrink)

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This paper explores a line of argument against the classical paradigm incognitive science that is based upon properties of non-linear dynamical systems, especially in their chaotic and near-chaotic behavior. Systems of this kind are capable of generating information-rich macro behavior that could be useful to cognition. I argue that a brain operating at the edge of chaos could generate high-complexity cognition in this way. If this hypothesis is correct, then the symbolic processing methodology incognitive science (...) faces serious obstacles. A symbolic description of the mind will be extremely difficult, and even if it is achieved to some approximation, there will still be reasons for rejecting the hypothesis that the brain is in fact a symbolic processor. (shrink)

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Emotions, Embodied Cognition and the Adaptive Unconscious argues for the need to consider many other factors, drawn from disciplines such as socio-biology, evolutionary psychology, the study of the emotions, the adaptive unconscious, the senses and conscious deliberation in analysing the complex topography of social action and the making of things. These factors are taken as ecological conditions that shape the contemporary expression of complex societies, not as constraints on human plasticity Without 'foundations', complex society cannot exist nor less evolve. This (...) is the familiar pairing fromcomplexity theory: path dependency and dynamic emergence. Inter-disciplinary andcomplexity perspectives need to be incorporated into the social sciences. Routinely, sociologists think of social phenomena as a distinct field, expressed in the term: the 'social construction of' without apparent need to refer to other material, biological, psychological, material or ecological conditions or agents. This book shows how the familiar sociological dynamics of identity, solidarity, differentiation and communication are shaped through the persistent interaction of unconscious and affective processing with conscious deliberation in newly emergent contexts. It is this re-expression, not the surpassing, of human characteristics in contemporary social action that needs to re-inform a complex, ecological approach to the theory and methodologies of the social sciences. The book is intended for a postgraduate/research audience and doctoral students to introduce and synthesise inter-disciplinary contributions to research intocomplexity theory in the social sciences. (shrink)

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Readers of TopiCS are invited to join a debate about the utility of ideas and methods ofcomplexity science. The topics of debate include empirical instances of qualitative change incognitive activity and whether this empirical work demonstrates sufficiently the empirical flags ofcomplexity. In addition, new phenomena discovered bycomplexity scientists, and motivated bycomplexity theory, call into question some basic assumptions of conventionalcognitive science such as stable equilibria and homogeneous variance. The (...) articles and commentaries that appear in this issue also illustrate a new debate style format for topiCS. (shrink)

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This book illustrates the program of Logical-Informational Dynamics. Rational agents exploit the information available in the world in delicate ways, adopt a wide range of epistemic attitudes, and in that process, constantly change the world itself. Logical-Informational Dynamics is about logical systems putting such activities at center stage, focusing on the events by which we acquire information and change attitudes. Its contributions show many current logics of information and change at work, often in multi-agent settings where social behavior is essential, (...) and often stressing Johan van Benthem's pioneering work in establishing this program. However, this is not a Festschrift, but a rich tapestry for a field with a wealth of strands of its own. The reader will see the state of the art in such topics as information update, belief change, preference, learning over time, and strategic interaction in games. Moreover, no tight boundary has been enforced, and some chapters add more general mathematical or philosophical foundations or links to current trends in computer science. (shrink)

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The core issue of our target article concerns how relationalcomplexity should be assessed. We propose that assessments must be based on actualcognitive processes used in performing each step of a task.Complexity comparisons are important for the orderly interpretation of research findings. The links between relationalcomplexity theory and several other formulations, as well as its implications for neural functioning, connectionist models, the roles of knowledge, and individual and developmental differences, are considered.

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The paper presents evidence in bacteria for the utility of Godfrey-Smith’s environmentalcomplexity thesis, using certain kinds of signal transduction systems as proxies forcognitive/behavioralcomplexity. Microbiologists already accept that the number of signal transduction proteins in a bacterial genome indicates the level of ecologicalcomplexity to which the organism is subject: the more signalling proteins, the greater thecomplexity. Sheer numbers are not always a reliable indicator of behavioralcomplexity, however. The paper proposes (...) a new, ECT-based procedure for identifying, from genomic sequence and signalling repertoire, novel bacterial candidates likely to exhibit behavioralcomplexity in response to a complex ecological niche. (shrink)

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QualitativeComplexity offers a critique of the humanist paradigm in contemporary social theory. Drawing from sources in sociology, philosophy,complexity theory, 'fuzzy logic', systems theory,cognitive science and evolutionary biology, the authors present a new series of interdisciplinary perspectives on the sociology of complex, self-organizing structures.

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This chapter examines the scope and limits of the tractability argument. It argues for two claims. First, that when explored with appropriate care and attention, it becomes clear that the argument provides no good reason to prefer massive modularity to the more traditional rationalist alternative. Second, while it is denied that tractability considerations support massive modularity per se, this does not mean that they show nothing whatsoever. Careful analysis of tractability considerations suggests a range of characteristics that any plausible version (...) of psychological rationalism is likely to possess. The chapter proceeds as follows: Section 1 outlines and clarifies the general form of the tractability argument. Section 2 explains how massive modularity is supposed to resolve intractability worries. Sections 3 to 7 highlight the deficiencies of the main extant arguments for claiming that nonmodular mechanisms are intractable. Section 8 concludes by sketching some of the general characteristics that a plausible rationalist alternative to massive modularity — one capable of subserving tractablecognitive processes — is likely to possess. (shrink)

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