The dynamical patterns in mental phenomena have a characteristic suppleness&emdash;a looseness or softness that persistently resists precise formulation&emdash;which apparently underlies the frame problem of artificial intelligence. This suppleness also undermines contemporary philosophical functionalist attempts to define mental capacities. Living systems display an analogous form of supple dynamics. However, the supple dynamics of living systems have been captured in recent artificial life models, due to the emergent architecture of those models. This suggests that analogous emergent models might be able to explain (...) supple dynamics of mental phenomena. These emergent models of the supple mind, if successful, would refashion the nature of contemporary functionalism in the philosophy of mind. (shrink)

Aphids display an abundance of adaptations that are not easily studied in existing model systems. Here we review the biology of a new genomic model system, the pea aphid, Acyrthosiphon pisum. We then discuss several phenomena that are particularly accessible to study in the pea aphid: the developmental genetic basis of polyphenisms, aphid–bacterial symbioses, the genetics of adaptation and mechanisms of virus transmission. The pea aphid can be maintained in the laboratory and natural populations can be studied (...) in the field. These properties allow controlled experiments to be performed on problems of direct relevance to natural aphid populations. Combined with new genomic approaches, the pea aphid is poised to become an important model system for understanding the molecular and developmental basis of many ecologically and evolutionarily relevant problems. BioEssays 28: 747–755, 2006. © 2006 Wiley Periodicals, Inc. (shrink)

New research on affective computing aiming to develop computer systems that recognize and respond to affective states can also contribute to the issues raised by Coan. Research on how humans interact with computers, and computer models that automatically recognize affective states from features in our physiology, behaviour, and language, may provide insights on how emotions that are experienced and expressed come to be. For example, there is empirical evidence that affect recognition techniques using several modalities are more accurate than those (...) using a single modality, but it is not clear if these improvements are caused by superadditivity (i.e., emergence) or redundancy. (shrink)

Examining AI spirituality can illuminate problematic assumptions about human spirituality and AI cognition, suggest possible directions for AI development, reduce uncertainty about future AI, and yield a methodological lens sufficient to investigate human-AI sociotechnical interaction and morality. Incompatible philosophical assumptions about human spirituality and AI limit investigations of both and suggest a vast gulf between them. An emergentist approach can replace dualist assumptions about human spirituality and identify emergent behavior in AI computation to overcome overly reductionist assumptions about computation. Using (...) general systems theory to organize models of human experience yields insight into human morality and spirituality, upon which AI modeling can also draw. In this context, the pragmatist Josiah Royce’s semiotic philosophy of spirituality identifies unanticipated overlap between symbolic AI and spirituality and suggests criteria for a human-AI community focused on modeling morality that would result in an emergent Interpreter-Spirit sufficient to influence the ongoing development of human and AI morality and spirituality. (shrink)

The discussion over the roles of genes and environment on the phenotypical specification of organisms has held a central role in science philosophy since the late 19th century and has re‐emerged in today's debate over genetic determinism and developmental plasticity. In fin‐de‐siecle Vienna, this debate coincided with a philosophical debate over empiricism/materialism versus idealism/vitalism. Turn‐of‐the‐century Vienna's highly interdisciplinary environment was also the birthplace for the model system of the un‐opposed molar. The un‐opposed molar system features new tissue (...) formation at the roots of teeth and tooth drift once opposing teeth are lost. The un‐opposed molar model system was revived by a group of Viennese scientists who left Vienna during the Nazi period to address Vienna's questions about evolution and heredity and about genes and environment in Chicago's post‐WWII scientific exile community. Here we are using the colorful history of the un‐opposed molar to investigate the role of culture and method in the scientific evolution of a model system. BioEssays 29:819–830, 2007. © 2007 Wiley Periodicals, Inc. (shrink)

Natural languages make prolific use of conventional constituent‐ordering patterns to indicate “who did what to whom,” yet the mechanisms through which these regularities arise are not well understood. A series of recent experiments demonstrates that, when prompted to express meanings through silent gesture, people bypass native language conventions, revealing apparent biases underpinning word order usage, based on the semantic properties of the information to be conveyed. We extend the scope of these studies by focusing, experimentally and computationally, on the interpretation (...) of silent gesture. We show cross‐linguistic experimental evidence that people use variability in constituent order as a cue to obtain different interpretations. To illuminate the computational principles that govern interpretation of non‐conventional communication, we derive a Bayesian model of interpretation via biased inductive inference and estimate these biases from the experimental data. Our analyses suggest people's interpretations balance the ambiguity that is characteristic of emerging language systems, with ordering preferences that are skewed and asymmetric, but defeasible. (shrink)

Natural languages make prolific use of conventional constituent‐ordering patterns to indicate “who did what to whom,” yet the mechanisms through which these regularities arise are not well understood. A series of recent experiments demonstrates that, when prompted to express meanings through silent gesture, people bypass native language conventions, revealing apparent biases underpinning word order usage, based on the semantic properties of the information to be conveyed. We extend the scope of these studies by focusing, experimentally and computationally, on the interpretation (...) of silent gesture. We show cross‐linguistic experimental evidence that people use variability in constituent order as a cue to obtain different interpretations. To illuminate the computational principles that govern interpretation of non‐conventional communication, we derive a Bayesian model of interpretation via biased inductive inference and estimate these biases from the experimental data. Our analyses suggest people's interpretations balance the ambiguity that is characteristic of emerging language systems, with ordering preferences that are skewed and asymmetric, but defeasible. (shrink)

The acoel worm Symsagittifera roscoffensis, an early offshoot of the Bilateria and the only well‐studied marine acoel that lives in a photosymbiotic relationship, exhibits a centralized nervous system, brain regeneration, and a wide repertoire of complex behaviors such as circatidal rhythmicity, photo/geotaxis, and social interactions. While this animal can be collected by the thousands and is studied historically, significant progress is made over the last decade to develop it as an emerging marine model. The authors here present (...) the feasibility of culturing it in the laboratory and describe the progress made on different areas, including genomic and tissue architectures, highlighting the associated challenges. In light of these developments, and on the ability to access abundant synchronized embryos, the authors put forward S. roscoffensis as a marine system to revisit questions in the areas of photosymbiosis, regeneration, chronobiology, and the study of complex behaviors from a molecular and evolutionary perspective. (shrink)

Spatial evolutionary game theory explains how cooperative traits can survive the intense competition in biological systems. If the spatial distribution allows cooperators to interact with each other frequently, the benefits of cooperation will outweigh the losses due to exploitation by selfish organisms. However, for a cooperative behavior to get established in a system, it needs to be found initially in a sufficiently large cluster to allow a high frequency of intracooperator interactions. Since mutations are rare events, this poses the (...) question of how cooperation can arise in a biological system in the first place. We present a simple model which captures two concepts from genetics that can explain how evolution overcomes the emergence problem. The first concept is, often in nature, a gene may not express its phenotype except under specific environmental conditions, rendering it to be a “silent” gene. The second key idea is that a neutral gene, one that does not harm or improve an organism’s survival chances, can still spread through a population if it is physically near to another gene that is positively selected. Through these two ideas, our model offers a possible solution to the fundamental problem of emergence of cooperation in biological systems. (shrink)

As brightly shown by Mainzer [24], the science of complexity has many distinct origins in many disciplines. Those various origins has led to “an interdisciplinary methodology to explain the emergence of certain macroscopic phenomena via the nonlinear interactions of microscopic elements” (ibid.). This paper suggests that the parallel and strong expansion of modeling and simulation - especially after the Second World War and the subsequent development of computers - is a rationale which also can be counted as an explanation of (...) this emergence. With the benefit of hindsight, one can find three periods in the methodologies of modeling in the empirical sciences: 1st the simple modeling of the simple, 2nd the simple modeling of the complex, 3rd the complex modeling and simulation of the complex. Our main thesis is that the current spreading (since the 90’s) of complex computer simulations of systems of models (where a simulation is no more a step by step calculus of a unique logico-mathematical model) is another promising dimension of the science of complexity. Following this claim, we propose to distinguish three different types of computer simulations in the context of complex systems’ modeling. Finally, we show that these types of simulations lead to three different types of weak emergence, too. (shrink)

We consider processes of emergence within the conceptual framework of the Information Loss principle and the concepts of systems conserving information; systems compressing information; and systems amplifying information. We deal with the supposed incompatibility between emergence and computability tout-court. We distinguish between computational emergence, when computation acquires properties, and emergent computation, when computation emerges as a property. The focus is on emergence processes occurring within computational processes. Violations of Turing-computability such as non-explicitness and incompleteness are intended to represent partially the (...) properties of phenomenological emergence, such as logical openness, given by the observer’s cognitive role; structural dynamics where change regards rules rather than only values; and multi-modelling where multiple non-equivalent models are required to model such structural dynamics. In this way, we validate, from an epistemological viewpoint, models and simulations of phenomenological emergence where the sequence of events constitutes the natural, analogical non-Turing computation which a cognitive complex system can reproduce through learning. Reproducibility through learning is different from Turing-like computational iteration. This paper aims to open a new, non-reductionist understanding of the conceptual relationship between emergence and computability. (shrink)

Emergence is defined as a process which cannot be described by a fixed model, consisting of invariant distinctions. Hence emergence must be described by a meta‐model, representing the transition of one model to another one by means of a distinction dynamics. The dynamics of distinctions is based on the processes of variation and selection, resulting in an invariant distinction, which constrains the variety and thus defines a new system. A classification of emergence processes is proposed, based (...) on the following criteria: amount of variety, internality/ externality of variation and selection, number of levels, and contingency of constraint. It is argued that traditional formal and computational models are incapable of representing the more general types of emergence, but that it is possible to generalize them on the basis of the dynamics of distinctions. (shrink)

It is largely acknowledged that natural languages emerge not just from human brains but also from rich communities of interacting human brains (Senghas, ). Yet the precise role of such communities and such interaction in the emergence of core properties of language has largely gone uninvestigated in naturally emerging systems, leaving the few existing computational investigations of this issue at an artificial setting. Here, we take a step toward investigating the precise role of community structure in the emergence of (...) linguistic conventions with both naturalistic empirical data and computational modeling. We first show conventionalization of lexicons in two different classes of naturally emerging signed systems: (a) protolinguistic “homesigns” invented by linguistically isolated Deaf individuals, and (b) a natural sign language emerging in a recently formed rich Deaf community. We find that the latter conventionalized faster than the former. Second, we model conventionalization as a population of interacting individuals who adjust their probability of sign use in response to other individuals' actual sign use, following an independently motivated model of language learning (Yang, , ). Simulations suggest that a richer social network, like that of natural (signed) languages, conventionalizes faster than a sparser social network, like that of homesign systems. We discuss our behavioral and computational results in light of other work on language emergence, and other work of behavior on complex networks. (shrink)

In this article, I examine Luhmann’s, Bunge’s and others’ views on emergence, and argue that Luhmann’s epistemological construal of emergence in terms of Totalausschluss (total exclusion) is both ontologically flawed and detrimental to an appropriate understanding of the distinctive features of social emergence. By contrast, Bunge’s rational emergentism, his CESM model, and Wimsatt’s characterization of emergence as nonaggregativity provide a useful framework to investigate emergence. While researchers in the field of social theory and sociology tend to regard Luhmann as (...) the sole representative of systems theory, the latter has been characterized by its diversity, and the writings of such systems theorists as Mario Bunge deserve more (critical) attention from social researchers than they receive at present. Finally, this article suggests that the perennial debate over methodological individualism and holism in social science may make real progress if such ambiguous terms as reduction and reductionism are elucidated before they are employed. (shrink)

Computational modeling plays an increasingly important explanatory role in cases where we investigate systems or problems that exceed our native epistemic capacities. One clear case where technological enhancement is indispensable involves the study of complex systems.1 However, even in contexts where the number of parameters and interactions that define a problem is small, simple systems sometimes exhibit non-linear features which computational models can illustrate and track. In recent decades, computational models have been proposed as a way to assist us in (...) understanding emergent phenomena. (shrink)

Within the scientific study of spirituality there are substantial ambiguities and uncertainties about relevant concepts, terms, evidences, methods, and relationships. Different disciplinary approaches reveal or emphasize different aspects of spirituality, such as outcomes, behaviors, skills, ambitions, and beliefs. I argue that these aspects interdepend in a way that constitutes a “systems model of spirituality.” This model enables a more holistic understanding of the nature of spirituality, and suggests a new definition that disambiguates spirituality from related concepts such as (...) religion, cultural sophistication, and prosocial behavior in animals. It also exposes important open questions about the nature of spirituality. To support the emerging scientific approach to the study of spirituality, I propose the development of a “philosophy of spirituality” that can clarify the conceptual terrain, identify important research directions, and facilitate a comprehensive and interdisciplinary investigation into the nature, validity, and implications of spirituality's conceptual and practical entailments. (shrink)

Integrative systems biology is an emerging field that attempts to integrate computation, applied mathematics, engineering concepts and methods, and biological experimentation in order to model large-scale complex biochemical networks. The field is thus an important contemporary instance of an interdisciplinary approach to solving complex problems. Interdisciplinary science is a recent topic in the philosophy of science. Determining what is philosophically important and distinct about interdisciplinary practices requires detailed accounts of problem-solving practices that attempt to understand how specific practices (...) address the challenges and constraints of interdisciplinary research in different contexts. In this paper we draw from our 5-year empirical ethnographic study of two systems biology labs and their collaborations with experimental biologists to analyze a significant problem-solving approach in ISB, which we call adaptive problem solving. ISB lacks much of the methodological and theoretical resources usually found in disciplines in the natural sciences, such as methodological frameworks that prescribe reliable model-building processes. Researchers in our labs compensate for the lack of these and for the complexity of their problems by using a range of heuristics and experimenting with multiple methods and concepts from the background fields available to them. Using these resources researchers search out good techniques and practices for transforming intractable problems into potentially solvable ones. The relative freedom lab directors grant their researchers to explore methodological options and find good practices that suit their problems is not only a response to the complex interdisciplinary nature of the specific problem, but also provides the field itself with an opportunity to discover more general methodological approaches and develop theories of biological systems. Such developments in turn can help to establish the field as an identifiably distinct and successful approach to understanding biological systems. (shrink)

A new theoretical model of oncogenesis that incorporates a systemic view of biodynamics was developed and analyzed. According to our model, the emergent behavior at the cell population level is the result of nonlinear interactions between the neoplastic and immune subsystems. Our approach allows subsequent extensions of the model to span multiple levels of biological organization. The model opens the possibility of a flexible connection between the molecular and tissue level descriptions of oncogenesis.

Any description of the emergence and evolution of different types of meaning processes (semiosis, sensu C.S.Peirce) in living systems must be supported by a theoretical framework which makes it possible to understand the nature and dynamics of such processes. Here we propose that the emergence of semiosis of different kinds can be understood as resulting from fundamental interactions in a triadically-organized hierarchical process. To grasp these interactions, we develop a model grounded on Stanley Salthe's hierarchical structuralism. This model (...) can be applied to establish, in a general sense, a set of theoretical constraints for explaining the instantiation of different kinds of meaning processes (iconic, indexical, symbolic) in semiotic systems. We use it to model a semiotic process in the immune system, namely, B-cell activation, in order to offer insights into the heuristic role it can play in the development of explanations for specific semiotic processes. (shrink)

It is argued that the truth status of emergent properties of complex adaptive systems models should be based on an epistemology of proof by constructive verification and therefore on the ontological axioms of a non-realist logical system such as constructivism or intuitionism. ‘Emergent’ properties of complex adaptive systems models create particular epistemological and ontological challenges. These challenges bear directly on current debates in the philosophy of mathematics and in theoretical computer science. CAS research, with its emphasis on computer simulation, (...) is heavily reliant on models which explore the entailments of Formal Axiomatic Systems. The incompleteness results of G¨odel, the incomputability results of Turing, and the Algorithmic Information Theory results of Chaitin, undermine a realist truth model of emergent properties. These same findings support the hegemony of epistemology over ontology and point to alternative truth models such as intuitionism, constructivism and quasi-empiricism. (shrink)

The analysis of genetic and epigenetic mechanisms of the genotype–phenotypic connection has, so far, only been possible in a handful of genetic model systems. Recent technological advances, including next‐generation sequencing methods such as RNA‐seq, ChIP‐seq and RAD‐seq, and genome‐editing approaches including CRISPR‐Cas, now permit to address these fundamental questions of biology also in organisms that have been studied in their natural habitats. We provide an overview of the benefits and drawbacks of these novel techniques and experimental approaches that can (...) now be applied to ecological and evolutionary vertebrate models such as sticklebacks and cichlid fish. We can anticipate that these new methods will increase the understanding of the genetic and epigenetic factors influencing adaptations and phenotypic variation in ecological settings. These new arrows in the methodological quiver of ecologist will drastically increase the understanding of the genetic basis of adaptive traits – leading to a further closing of the genotype–phenotype gap. -/- . (shrink)

In this article, I examine Luhmann’s, Bunge’s and others’ views on emergence, and argue that Luhmann’s epistemological construal of emergence in terms of Totalausschluss (total exclusion) is both ontologically flawed and detrimental to an appropriate understanding of the distinctive features of social emergence. By contrast, Bunge’s rational emergentism, his CESM model, and Wimsatt’s characterization of emergence as nonaggregativity provide a useful framework to investigate emergence. While researchers in the field of social theory and sociology tend to regard Luhmann as (...) the sole representative of systems theory, the latter has been characterized by its diversity, and the writings of such systems theorists as Mario Bunge deserve more (critical) attention from social researchers than they receive at present. Finally, this article suggests that the perennial debate over methodological individualism and holism in social science may make real progress if such ambiguous terms as reduction and reductionism are elucidated before they are employed. (shrink)

Modularity in the human brain remains a controversial issue, with disagreement over the nature of the modules that exist, and why, when, and how they emerge. It is a natural assumption that modularity offers some form of computational advantage, and hence evolution by natural selection has translated those advantages into the kind of modular neural structures familiar to cognitive scientists. However, simulations of the evolution of simplified neural systems have shown that, in many cases, it is actually non-modular architectures that (...) are most efficient. In this paper, the relevant issues are discussed and a series of simulations are presented that reveal crucial dependencies on the details of the learning algorithms and tasks that are being modelled, and the importance of taking into account known physical brain constraints, such as the degree of neural connectivity. A pattern is established which provides one explanation of why modularity should emerge reliably across a range of neural processing tasks. (shrink)

Collaborative Governance Organizations (CGOs) are commonly established to manage Socio-Ecological Systems (SESs). Collaborative processes are designed to gather information relevant to SESs from a diverse set of actors and to foster shared learning in the face of ecological adversity. Little is known, however, about how CGOs develop attention to emerging ecological adversity, which is critical for providing effective and timely responses that enhance SES resilience. The biophysical mechanisms driving emerging ecological adversity cut across a wide range of spatial (...) and temporal scales. Developing attention to these mechanisms requires identifying cross-scale interdependencies and allocating limited attentional resources between local vs. global concerns, and short-term vs. long-term issues. This study explores the process of developing organizational attention to climate change in French river basins. We propose a model in which CGOs’ systemic attention develops through key interactions with the State, scientific councils, and their biophysical environment. (shrink)

Self-organized criticality (SOC) is based upon the idea that complex behavior can develop spontaneously in certain multi-body systems whose dynamics vary abruptly. This book is a clear and concise introduction to the field of self-organized criticality, and contains an overview of the main research results. The author begins with an examination of what is meant by SOC, and the systems in which it can occur. He then presents and analyzes computer models to describe a number of systems, and he explains (...) the different mathematical formalisms developed to understand SOC. The final chapter assesses the impact of this field of study, and highlights some key areas of new research. The author assumes no previous knowledge of the field, and the book contains several exercises. It will be ideal as a textbook for graduate students taking physics, engineering, or mathematical biology courses in nonlinear science or complexity. (shrink)

This chapter describes the application of reduction concepts in emergence and self organization of complex dynamical system. Condition-dependent laws compress and dynamical equation sets provide implicit compressed representations even when most of that information is not explicitly available without decompression. And, paradoxically, there is still the determined march of fundamental analytical dynamics expanding its compression reach toward a Theory of Everything—even while the more rapidly expanding domain of complex systems dynamics confronts its assumptions and its monolithicity. Nor does science (...) fall apart into a disunified aggregate of particular cases since, with fundamental dynamics as a backbone, complex matching up of models across theoretical and empirical domains then articulates its model-structured skeleton. Discussion provides the delicately entwined dance of emergence and reduction providing constraints on compression that also permit its expansion. However, while the vision is not dead, it is currently substantially more complexly structured through model similarities and differences than that initially envisaged and individuals are left with deep questions about compression unresolved. (shrink)

We present here a digital scenario to simulate the emergence of self-organized symbol-based communication among artificial creatures inhabiting a virtual world of predatory events. In order to design the environment and creatures, we seek theoretical and empirical constraints from C.S.Peirce Semiotics and an ethological case study of communication among animals. Our results show that the creatures, assuming the role of sign users and learners, behave collectively as a complex system, where self-organization of communicative interactions plays a major role in (...) the emergence of symbol-based communication. We also strive for a careful use of the theoretical concepts involved, including the concepts of symbol, communication, and emergence, and we use a multi-level model as a basis for the interpretation of inter-level relationships in the semiotic processes we are studying. (shrink)

The autocell proposal for the emergence of life and natural selection through the interaction of two reciprocally coupled self-organizing processes specifically provides a protein-first model for the origin of life that can be explored by computer simulations and experiment. Beyond the specific proposal it can be considered more generally as a thought experiment in which the principles deduced for the autocell could apply to other possible detailed chemical scenarios of catalytic polymers and protometabolism, including living systems emerging within (...) membranelike barriers. The autocell model allows for the analysis of the emergence of not only agency and purpose but also of interpretation and semiosis as true living systems arise. (shrink)

The aim of this work is to present aggregation methods of hierarchically organized systems allowing one to replace the initial micro-system by a macro-system described by a few global variables. We also study the relations between the fast micro-dynamics and the slow macro-dynamics which can produce global properties. Emergence corresponds to a bottom-up coupling that is the result effected by a micro-level at a macro-level. As an example, we present prey-predator models with different time scales in an heterogeneous (...) environment. A fast time scale is associated to the migration process on spatial patches and a slow time scale is associated to growth and interactions between the populations. Preys must go on spatial patches where resources are located and where predators can attack them. The efficiency of the predators to catch preys is patch dependent. Perturbation methods allow us to aggregate the initial system of differential equations for the patch sub-populations into a macro-system of two differential equations governing the total population densities. We study the case of density independent and density dependent migrations. In the latter case, we show that different functional responses can emerge in the macro prey-predator model as a result of the coupling between the slow and fast systems. (shrink)

Awareness is a concept that has been frequently studied in the context of Computer Supported Cooperative Work. However, other fields of computer science can benefit from this concept. Recent research in the multi-agent systems field has highlighted the relevance of complex interaction models such as multi-party communication and context awareness for simulation and adaptive systems. In this article, we present a generic interaction model that enables to use these different models in a standardized way. Emerging as a first-order (...) abstraction, the environment, in the sense of a common medium for the agents, is a suitable paradigm to support the agents’ awareness. We present an operational model, called Environment as Active Support of Interaction, to take into account all the agents that can be interested in a communication. This model is then extended for the regulation of multiagent systems interactions. Priority policies are given to manage the rules governing the context (un-)awareness of the agents. We also present a new AUML connector to create protocols that take into account the agent awareness to implement proactive behaviour, and several communication scenarios are proposed to show practical applications of this model. (shrink)

The Emergic Cognitive Model (ECM) is a unified computational model of visual filling-in based on the Emergic Network architecture. The Emergic Network was designed to help realize systems undergoing continuous change. In this thesis, eight different filling-in phenomena are demonstrated under a regime of continuous eye movement (and under static eye conditions as well). -/- ECM indirectly demonstrates the power of unification inherent with Emergic Networks when cognition is decomposed according to finer-grained functions supporting change. These can interact (...) to raise additional emergent behaviours via cognitive re-use, hence the Emergic prefix throughout. Nevertheless, the model is robust and parameter free. Differential re-use occurs in the nature of model interaction with a particular testing paradigm. -/- ECM has a novel decomposition due to the requirements of handling motion and of supporting unified modelling via finer functional grains. The breadth of phenomenal behaviour covered is largely to lend credence to our novel decomposition. -/- The Emergic Network architecture is a hybrid between classical connectionism and classical computationalism that facilitates the construction of unified cognitive models. It helps cutting up of functionalism into finer-grains distributed over space (by harnessing massive recurrence) and over time (by harnessing continuous change), yet simplifies by using standard computer code to focus on the interaction of information flows. Thus while the structure of the network looks neurocentric, the dynamics are best understood in flowcentric terms. Surprisingly, dynamic system analysis (as usually understood) is not involved. An Emergic Network is engineered much like straightforward software or hardware systems that deal with continuously varying inputs. Ultimately, this thesis addresses the problem of reduction and induction over complex systems, and the Emergic Network architecture is merely a tool to assist in this epistemic endeavour. -/- ECM is strictly a sensory model and apart from perception, yet it is informed by phenomenology. It addresses the attribution problem of how much of a phenomenon is best explained at a sensory level of analysis, rather than at a perceptual one. As the causal information flows are stable under eye movement, we hypothesize that they are the locus of consciousness, howsoever it is ultimately realized. (shrink)

In this paper, the current AI view that emergent functionalities apply only to the study of subcognitive agents is questioned; a hypercognitive view of autonomous agents as proposed in some AI subareas is also rejected. As an alternative view, a unified theory of social interaction is proposed which allows for the consideration of both cognitive and extracognitive social relations. A notion of functional effect is proposed, and the application of a formal model of cooperation is illustrated. Functional cooperation shows (...) the role of extracognitive phenomena in the interaction of intelligent agents, thus representing a typical example of emergent functionality. (shrink)

Within today's emerging global society, educational systemic change is a dynamic, complex process that must seek to engage active participation of all stakeholders. This article examines alternative models of this process, providing different perspectives of the recursive and comprehensive nature of change when viewed from the vantage points of those stakeholders within the process. An envisioned school or educational system that addresses preparation of a citizenry dedicated to democratic principles and issues of social justice must consciously examine the (...) relationships, that form and reform interconnecting and unifying diverse subsystems within the school's constructed meaning and purpose. (shrink)

Standard semantic information processing models—information in; information processed; information out —lend themselves to standard models of the functioning of the brain in terms, e.g., of threshold-switch neurons connected via classical synapses. That is, in terms of sophisticated descendants of McCulloch and Pitts models. I argue that both the cognition and the brain sides of this framework are incorrect: cognition and thought are not constituted as forms of semantic information processing, and the brain does not function in terms of passive input (...) processing units organized as neural nets. An alternative framework is developed that models cognition and thought not in terms of semantic information processing, and, correspondingly, models brain functional processes also not in terms of semantic information processing. As alternative to such models: I outline a pragmatist oriented, interaction based, model of representation; derive from this model a fundamental framework of constraints on how the brain must function; show that such a framework is in fact found in the brain, and develop the outlines of a broader model of how mental processes can be realized within this alternative framework. Part I of this discussion focuses on some criticisms of standard modeling frameworks for representation and cognition, and outlines an alternative interactivist, pragmatist oriented, model. In part II, the focus is on the fact that the brain does not, in fact, function in accordance with standard passive input processing models—e.g., information processing models. Instead, there are multiple endogenously active processes at multiple spatial and temporal scales across multiple kinds of cells. A micro-functional model that accounts for, and even predicts, these multi-scale phenomena in generating emergent representation and cognition is outlined. That is, I argue that the interactivist model of representation outlined offers constraints on how the brain should function that are in fact empirically found, and, in reverse, that the multifarious details of brain functioning entail the pragmatist representational model—a very strong interrelationship. In the sequel paper, starting with part III, this model is extended to address macro-functioning in the CNS. In part IV, I offer a discussion of an approach to brain functioning that has some similarities with, as well as differences from, the model presented here: sometimes called the predictive brain approach. (shrink)

The received view about emergence and reduction is that they are incompatible categories. I argue in this paper that, contrary to the received view, emergence and reduction can hold together. To support this thesis, I focus attention on dynamical systems and, on the basis of a general representation theorem, I argue that, as far as these systems are concerned, the emulation relationship is sufficient for reduction (intuitively, a dynamical system DS1 emulates a second dynamical system DS2 when DS1 (...) exactly reproduces the whole dynamics of DS2). This representational view of reduction, contrary to the standard deductivist one, is compatible with the existence of structural properties of the reduced system that are not also properties of the reducing one. Therefore, under this view, by no means are reduction and emergence incompatible categories but, rather, complementary ones. (shrink)

This paper proposes a prolegomenal model for the mechanisms through which new styles and schools of art – Cubism or conceptual art, for example – undergo the catalytic, evental transition from potential to actual. The model proposed herein, of fine art as a complex adaptive system that emerges and grows in a manner analogous to that of certain specific forms of biological organization, is predicated on a shift from the residual traces of Greenbergian disciplinary and mediumistic differentiation (...) – grounded in an analytic autonomy – to modes of interaction and aesthetic signal exchange emergent from an autopoietic autonomy – a systemic process of autocatalysis and transformation similar to the recursively generative feedback relations seen in cell metabolism and in ecosystems. This conceptual recalibration leads to a model of artistic eventalization and change that algorithmically unfolds from the adjacent possible as an emergent phenomenon, analogous to the aggregative and spontaneous, self-organizational swarm behavior seen in the flocking of birds or the schooling of fish, applied here to schools of art. (shrink)

The purpose of the article is to analyze the concept of contextual emergence as well as its selected applications in philosophy of mind and cognitive science. In the first section the author presents the general assumptions of the emergentist model of reality. He stresses that the concept of emergence can be applied to the description of various levels of organization of nature: one of these levels is that of mental-cognitive processes, analyzed within the fields of philosophy of mind and (...) cognitive science. In the subsequent sections, he introduces the definitions of contextual emergence and systemic causation and he points to their selected applications to mentalcognitive systems. In the concluding part, he presents the ideas of Gerald Edelman and Michael Gazzaniga on the role of contextual explanations as well as the concepts of emergence in the philosophy of biology and cognitive neuroscience. He also indicates the possibility of incorporating the concept of contextual emergence into active externalism and the extended cognition theory. (shrink)

Robert Rosen has proposed several characteristics to distinguish “simple” physical systems (or “mechanisms”) from “complex” systems, such as living systems, which he calls “organisms”. The Memory Evolutive Systems (MES) introduced by the authors in preceding papers are shown to provide a mathematical model, based on category theory, which satisfies his characteristics of organisms, in particular the merger of the Aristotelian causes. Moreover they identify the condition for the emergence of objects and systems of increasing complexity. As an application, the (...) cognitive system of an animal is modeled by the “MES of cat-neurons” obtained by successive complexifications of his neural system, in which the emergence of higher order cognitive processes gives support to Mario Bunge’s “emergentist monism.”. (shrink)

This paper presents a proof of concept for a graphical models approach to assessing the moral coherence and moral robustness of systems of social interactions. “Moral coherence” refers to the degree to which the rights and duties of agents within a system are effectively respected when agents in the system comply with the rights and duties that are recognized as in force for the relevant context of interaction. “Moral robustness” refers to the degree to which a system (...) of social interaction is configured to ensure that the interests of agents are effectively respected even in the face of noncompliance. Using the case of conscientious objection of pharmacists to filling prescriptions for emergency contraception as an example, we illustrate how a graphical models approach can help stakeholders identify structural weaknesses in systems of social interaction and evaluate the relative merits of alternate organizational structures. By illustrating the merits of a graphical models approach we hope to spur further developments in this area. (shrink)

Critical analyses of current food systems underline the need to respond to important challenges in questions of nutritional health, environmental sustainability, socio-economic development and protection of the cultural wealth. A wide range of perspectives and methodologies were used to carry out those analyses yielding a significant variety of proposals to undertake the challenges. In most of those analyses, the need to transform our current food systems both from the local to the global level is emphasized, paying attention to food chain (...) processes as well as to decision-makers. The analysis presented in this paper reflects specifically on those proposals based on a common aspect: the need to transform the governance of the EU present-day food system, that is, who makes decisions, how are those decisions made, and which changes need to be made to empower food consumers. The introduction of reforms to change these models is proposed. The focus of these proposals, including those that argue in favour of food sovereignty, the human right to food or the acknowledgement of a food citizenship, share, I believe, a common key. All of them advocate transformations in models of food governance on the basis of a series of mechanisms and principles which for centuries have been employed to control power and grant the governed a status digno vis-à-vis those who govern. Within those proposals we may identify an incipient food constitutionalism, which I will address along with the opportunities and obstacles inherent in the current EU Legal Framework. (shrink)

The American food system has come to be defined by three significant developments: globalization, consolidation, and industrialization. These developments have not emerged as defining elements of t...

Ranging from miniaturized biological robots to organoids, multi-cellular engineered living systems (M-CELS) pose complex ethical and societal challenges. Some of these challenges, such as how to best distribute risks and benefits, are likely to arise in the development of any new technology. Other challenges arise specifically because of the particular characteristics of M-CELS. For example, as an engineered living system becomes increasingly complex, it may provoke societal debate about its moral considerability, perhaps necessitating protection from harm or recognition of (...) positive moral and legal rights, particularly if derived from cells of human origin. The use of emergence-based principles in M-CELS development may also create unique challenges, making the technology difficult to fully control or predict in the laboratory as well as in applied medical or environmental settings. In response to these challenges, we argue that the M-CELS community has an obligation to systematically address the ethical and societal aspects of research and to seek input from and accountability to a broad range of stakeholders and publics. As a newly developing field, M-CELS has a significant opportunity to integrate ethically responsible norms and standards into its research and development practices from the start. With the aim of seizing this opportunity, we identify two general kinds of salient ethical issues arising from M-CELS research, and then present a set of commitments to and strategies for addressing these issues. If adopted, these commitments and strategies would help define M-CELS as not only an innovative field, but also as a model for responsible research and engineering. (shrink)

First, a principal distinction between two different kinds of semiotic investigations is introduced, both required in the study of living signs and signs of life. Then, the attempt within the new field of Artificial Life to model and synthesise computationally based living systems is discussed with special attention paid to the possible emergence of genuine life-like behaviour in such models of for instance self-reproduction. Remarks will be made on a seemingly odd aspect of the biological concept of life; that (...) it is not as coherent as normally conceived of. In general, biosemiotic emergence of new sign functions is distinguished from other kinds of emergence that pertain to the domain of the observer and the modeling relation. (shrink)