The input data to grammar learning algorithms often consist of overt forms that do not contain full structural descriptions. This lack of information may contribute to the failure of learning. Past work on Optimality Theory introduced Robust Interpretive Parsing (RIP) as a partial solution to this problem. We generalize RIP and suggest replacing the winner candidate with a weighted mean violation of the potential winner candidates. A Boltzmann distribution is introduced on the winner set, and the distribution’s parameter $T$ is (...) gradually decreased. Finally, we show that GRIP, the Generalized Robust Interpretive Parsing Algorithm significantly improves the learning success rate in a model with standard constraints for metrical stress assignment. (shrink)

If the problem of the origin of life is conceptualized as a process of emergence of biochemistry from proto-biochemistry, which in turn emerged from the organic chemistry and geochemistry of primitive earth, then the resources of the new sciences of complex systems dynamics can provide a more robust conceptual framework within which to explore the possible pathways of chemical complexification leading to living systems and biosemiosis. In such a view the emergence of life, and concomitantly of natural selection and biosemiosis, (...) is the result of deep natural laws (the outlines of which we are only beginning to perceive) and reflects a degree of holism in those systems that led to life. Further, such an approach may lead to the development of a more general theory of biology and of natural organization, one informed by semiotic concepts. (shrink)

The design argument was rebutted by David Hume. He argued that the world and its contents (such as organisms) were not analogous to human artifacts. Hume further suggested that there were equally plausible alternatives to design to explain the organized complexity of the cosmos, such as random processes in multiple universes, or that matter could have inherent properties to self-organize, absent any external crafting. William Paley, writing after Hume, argued that the functional complexity of living beings, however, defied naturalistic explanations. (...) In effect he dared anyone to come up with an alternative to his inference to design, and hence a designer, outside of nature. Charles Darwin explained the apparent design of functional complexity by his theory of natural selection. Asa Gray, however, in essays as well as in correspondence with Darwin argued that natural selection allowed for a type of ' evolutionary teleology' in which design at most could be considered the result of universal principles. F. E. Hicks updated Hume by specifically objecting to the use of design arguments by Paley. Hicks argued that the apparent design seen in nature reflected order at a deep level in nature. The design argument was briefly revived by Lawrence Henderson early in the twentieth century but he ultimately concluded that design and teleology were not necessarily mutually entailing and he retracted his design argument in favor of one that he termed ' natural teleology'. The current claims of ' intelligent design' have the same logical problems that have beset previous design arguments. If design is divorced from teleology and its discontents put behind us, then there is a possibility that the latter can have a place in the development of theories to explain the phenomena of emergent complexity. (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)

Although computational models of cognitive agents that incorporate a wide range of cognitive functionalities have been developed in cognitive science, most of the work in social simulation still assumes rudimentary cognition on the part of the agents. In contrast, in this work, the interaction of cognition and social structures/processes is explored, through simulating survival strategies of tribal societies. The results of the simulation demonstrate interactions between cognitive and social factors. For example, we show that cognitive capabilities and tendencies may be (...) relevant to what social institutions may be adopted. This work points to a cognitively based approach towards social simulation, as well as a new area of research—exploring the cognitive–social interaction through cognitively based social simulation. (shrink)

This paper discusses the possibility of wealth adjustment through a credit network. The discussed credit network in this paper is a kind of loaning with no interest rate (its value is zero). It explains the influence of existence or inexistence of a cooperation originated from the credit network on wealth distribution and adjustment in an artificial society. To show how the wealth may distribute, environment agents in terms of their obtained wealth have been classified into ten wealth categories; thus, the (...) share of each category in terms of population has been determined. In addition, the survival of population in the environment has been studied. Findings and results show more balanced distribution of agents among the categories of wealth and higher survival of the population in the existence of the credit network. More over, the curve of population has fewer fluctuations. In other words, the population is more stable due to the ability of credit network in making more survival and stability in the population of environment in periods of time by providing the possibility of cooperation and wealth better distribution. (shrink)

Wealth distribution based on classic sugarscape model leads to a population increase and the Gini coefficient decrease when cooperation and communication parameters are taken into account. In another study, this model was developed by implying a receipt of one-fifth of the assets of the population and derived utilization for poor people. The results showed a relation between mortality decrease, population increase, and Gini coefficient decrease (equality increase). In a synergic process, the wealth adjustment based on sugarscape model underwent some experiments (...) by implying communication and cooperation, and the mechanism of receiving and utilizing the assets. The results show that the population increase and the Gini coefficient decrease play an important role in wealth adjustment. (shrink)

Volume 19, Issue 3, June 2020, Page 207-216.

Populism is currently one of the most studied socio-political topics. However, no shared definition is present at the moment. Fortunately, common features are emerging in recent studies, so that the possibility to devise a comprehensive concept of populism does not seem illusory anymore. In this article I evaluate whether an ontological determination of the concept is conceivable, according to a critical and dynamical perspective. This means that epistemological questions are considered as fundamental, and ontology looks at dynamical systems theories in (...) order to conceptually organize the outcomes of scientific researches. Taking advantage of ontological and system theoretic categories, I try to delineate some not obvious issues in the current approaches to populism. (shrink)

Complexity theory challenges educational philosophy to reconsider accepted paradigms of teaching, learning and educational research. However, though attractive, not least because of its critique of positivism, its affinity to Dewey and Habermas, and its arguments for openness, diversity, relationships, agency and creativity, the theory is not without its difficulties. These are seen to lie in terms of complexity theory's nature, status, methodology, utility and contribution to the philosophy of education, being a descriptive theory that is easily misunderstood as a prescriptive (...) theory, silent on key issues of values and ethics that educational philosophy should embrace, of questionable internal consistency, and of limited ‘added value’ in educational philosophy. The paper sets out key tenets of complexity theory and argues that, though it is useful for educational philosophy, it requires new conceptual tools and mind‐sets to comprehend fully its significance. (shrink)

The gastrointestinal tract is normally investigated using reductionism methods in human studies, where the focus is on each segment of the gastrointestinal system and the specific links between various parts of it. This helps researchers and clinicians to produce a simple relationship between the elements of the gastrointestinal tract based on clinical diagnosis and treatment. However, there is evidence indicating that the gastrointestinal tract has properties that are beyond function of the simple systems, such as, multiplicity of elements, network communication, (...) emergence, self-organization, sudden transition, nonlinearity, and adaptation, all of which are attributes of complex systems. It seems that the gastrointestinal tract is an appropriate candidate for complexity research. If the gastrointestinal tract is assumed as a complex system, then it would be more fitting to study the tract using holistic methods through interdisciplinary perspective. In the present paper, the features of the gastrointestinal that correlate to complex systems have been explained using physiological examples from studies done on human subjects. (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)

The common opinion has been that evolution results in the continuing development of more complex forms of life, generally understood as more complex organisms. The arguments supporting that opinion have recently come under scrutiny and been found wanting. Nevertheless, the appearance of increasing complexity remains. So, is there some sense in which evolution does grow complexity? Artificial life simulations have consistently failed to reproduce even the appearance of increasing complexity, which poses a challenge. Simulations, as much as scientific theories, are (...) obligated at least to save the appearances! We suggest a relation between these two problems, understanding biological complexity growth and the failure to model even its appearances. We present a different understanding of that complexity which evolution grows, one that genuinely runs counter to entropy and has thus far eluded proper analysis in information-theoretic terms. This complexity is reflected best in the increase in niches within the biosystem as a whole. Past and current artificial life simulations lack the resources with which to grow niches and so to reproduce evolution’s complexity. We propose a more suitable simulation design integrating environments and organisms, allowing old niches to change and new ones to emerge. (shrink)

The intuitive difference between a system that choreographs the motion of its parts in the service of goals of its own formulation and a system composed of a collection of parts doing their own thing without coordination has been shaken by now familiar examples of self-organization. There is a broad and growing presumption in parts of philosophy and across the sciences that the appearance of centralized information-processing and control in the service of system-wide goals is mere appearance, i.e., an explanatory (...) heuristic we have evolved to predict behavior, but one that will eventually get swept away in the advancing tide of self-organization. I argue that there is a distinction of central importance here, and that no adequate science of complex systems can dispense with it. (shrink)

As a significant extension of our previous calculus of logical differentials and moving logic, we propose here a mathematical diagram for specifying the emergence of novelty, through the construction of some “differentials” related to cohomological computations. Later we intend to examine how to use these “differentials” in the analysis of anticipation or evolution schemes. This proposal is given as a consequence of our comments on the Ehresmann–Vanbremeersch’s work on memory evolutive systems, from the two points of view which are characterization (...) of life and use of categorical modeling. It would not be possible to conceive of the “differentials” outside the frame of a MES. Furthermore, we hope that this diagram will be useful to exhibit the “emergence of sense” in discourses, and this idea is supported here by a brief examination of how a discourse could be seen as a living system. (shrink)

Reductionism has dominated science and philosophy for centuries. Complexity has recently shown that interactions—which reductionism neglects—are relevant for understanding phenomena. When interactions are considered, reductionism becomes limited in several aspects. In this paper, I argue that interactions imply nonreductionism, non-materialism, non-predictability, non-Platonism, and non-Nihilism. As alternatives to each of these, holism, informism, adaptation, contextuality, and meaningfulness are put forward, respectively. A worldview that includes interactions not only describes better our world, but can help to solve many open scientific, philosophical, and (...) social problems caused by implications of reductionism. (shrink)

In the last decade, Systems Biology has emerged as a conceptual and explanatory alternative to reductionist-based approaches in molecular biology. However, the foundations of this new discipline need to be fleshed out more carefully. In this paper, we claim that a relational ontology is a necessary tool to ground both the conceptual and explanatory aspects of Systems Biology. A relational ontology holds that relations are prior—both conceptually and explanatory—to entities, and that in the biological realm entities are defined primarily by (...) the context they are embedded within—and hence by the web of relations they are part of. (shrink)

Although the role of morphology in evolutionary theory remains a subject of debate, assessing the contributions of morphological investigation to evolutionary developmental biology (Evo-devo) is a more circumscribed issue of direct relevance to ongoing research. Historical studies of morphologically oriented researchers and the formation of the Modern Synthesis in the Anglo-American context identify a recurring theme: the synthetic theory of evolution did not capture multiple levels of biological organization. When this feature is incorporated into a philosophical framework for explaining the (...) origin of evolutionary innovations and novelties (a core domain of inquiry in Evo-devo) two specific roles for morphology can be described: (1) the conceptualization and operational identification of the targets of explanation; and (2) the elucidation of causal interactions at higher levels of organization during ontogeny and through evolutionary time. These roles are critical components of any adequate explanation of innovation and novelty though not exhaustive of the parts played by morphology in evolutionary investigation. They also invite reflection on what counts as an evolutionary cause in contemporary evolutionary biology. (shrink)

It is becoming ever more accepted that investigations of mind span the brain, body, and environment. To broaden the scope of what is relevant in such investigations is to increase the amount of data scientists must reckon with. Thus, a major challenge facing scientists who study the mind is how to make big data intelligible both within and between fields. One way to face this challenge is to structure the data within a framework and to make it intelligible by means (...) of a common theory. Radical embodied cognitive neuroscience can function as such a framework, with dynamical systems theory as its methodology, and self-organized criticality as its theory. (shrink)

The quest of developing the logistics discipline, with a more theoretical foundation, is something several authors have emphasized and called for. Today one could argue that most of the research on logistics has a strong connection to the positivistic paradigm where there is a great emphasis on prediction, rationality and control in the solutions produced. In order to challenge the common assumptions and develop the logistics discipline, the process of knowledge creation i.e. the epistemological considerations, are central. Since a paradigm (...) consists of metatheoretical assumptions i.e. ontology and epistemology, the paradigmatic question is the key in order to change the frame of reference of the logistics discipline. The overall purpose of this licentiate thesis is to propose a paradigmatic view and a pragmatic approach based on the science of complexity that contribute to the further development of the logistics discipline. Two main methods have been used; one focusing on my main research method, which is my study of literature related to the field, and the other on the empirically oriented case studies that have been conducted The paradigmatic view proposed in this thesis is based on insights gained from the science of complexity. Assumptions made concerning how to approach and transfer knowledge attained from our perceived reality, drive the choices of methods when conducting research and have, of course, great influence on the results obtained and presented from any research process. Adopting a complexity perspective means taking a step away from the common positivistic influenced view, which dominates the logistics discipline, and approaching the phenomena of interest with a different set of assumptions and prerequisites in the research process. This set of assumptions is in line with the complex adaptive system platform developed in the thesis. The CAS platform is the foundation for the proposed pragmatic approach. The first properties of the proposed platform i.e. the CAS feature covering internal properties, are of central importance in order to grasp fully the complexity of a studied system and to understand where it is derived from. The proposed pragmatic approach means vi taking into consideration the smallest elements of, and agents relevant to, the study being conducted. From this internal approach the mindset of the researcher or practitioner is of great importance in the event of what such an approach might reveal about the problem being studied. In order to capture emergent phenomena and identify self-organization on different levels of description, we need a perception of the context as being “gray”; that is not considering the context as something which is static or stable, nor as something totally disoriented and uncontrollable. The metaphorical description of a fitness landscape where coevolution and continuous changes caused by the actions performed by agents inside and outside the perceived system under study, could be beneficial in the research process. This is the case since too many reductions of various factors could result in “far-from-reality” based solutions. The fundamental aspects of the pragmatic approach are a bottom-up perspective, where the smallest elements relevant to a certain logistics problem are considered, the system built up from this and, of course, an alignment with the paradigmatic view based on the science of complexity. (shrink)

In this thesis I present a virtual laboratory which implements five different models for controlling animats: a rule-based system, a behaviour-based system, a concept-based system, a neural network, and a Braitenberg architecture. Through different experiments, I compare the performance of the models and conclude that there is no best model, since different models are better for different things in different contexts. The models I chose, although quite simple, represent different approaches for studying cognition. Using the results as an empirical philosophical (...) aid, I note that there is no best approach for studying cognition, since different approaches have all advantages and disadvantages, because they study different aspects of cognition from different contexts. This has implications for current debates on proper approaches for cognition: all approaches are a bit proper, but none will be proper enough. I draw remarks on the notion of cognition abstracting from all the approaches used to study it, and propose a simple classification for different types of cognition. (shrink)

Logistics is gaining increased attention in companies since interconnectivity is increasing, and the interdependence among actors is enhanced due to challenges organizations are facing today . While the logistics discipline has been characterized by an efficiency focus based on positivistic assumptions, the challenges of today require a focus on effectiveness i.e. adaptive logistics based on extended assumptions. As firms are becoming more complex themselves in their relationships with suppliers and customers, and there is increased turbulence facing almost all industries, this (...) complexity needs to be taken into consideration by logistics researchers and practitioners in order to increase their understanding, and for the sense-making of logistics phenomena. The purpose of the thesis is to contribute to the further development of logistics research and practice by exploring, from a complexity perspective, how increased adaptation can enhance logistics effectiveness. In order to gain knowledge and understanding of how a complexity perspective could impact logistics, several methods have been used. Through extensive literature reviews from several disciplines, insights into what type of underlying assumptions dominates the discipline were gained. In order to understand logistics in its ?real? empirical setting, a topical study entitled ?real logistics? was performed, in which logistics practitioners were interviewed with a grounded theory-inspired approach. Case studies have also been performed, focusing on issues of effectiveness. Furthermore, for me to be able provide the logistics discipline with an approach which is ?proven? to be applicable and where ?operationalization? of the complexity perspective could be achieved, combined case and simulation studies have been performed. It is the firm conclusion that adaptive logistics is not a concept separated from human-mind and involvement, instead it is a transformative concept realized in the individual and collective sense-making processes guided by assumptions related to both filters. Hence, in order to move towards adaptive logistics it is the conclusion that this is a process involving reflections on assumptions and their impacts on logistics phenomena and processes, and operationalization of a new way of thinking through sense-making methods with close connection to the perceived contexts in question. For the reflective part, theoretical frameworks are needed, which are in line with assumptions similar to real-life experience by managers i.e. of a less mechanical character, with emphasis on the extended assumptions comprised in the complexity perspective. Secondly, in order to operationalize a different way of thinking and acting i.e. change mind-sets to embrace more complex considerations, and provide tangible results in a reasonable time period, it has been concluded that agent-based modeling provides a feasible and applicable method and tool. (shrink)

Este artículo hace una presentación de un tema que ha sido pasado por alto en la filosofía, la filosofía de la ciencia y las ciencias de la complejidad, a saber: la importancia de las ciencias sociales y el modo como pueden beneficiarse con las matemáticas de los sistemas dinámicos. Por tanto, el ar..

As science, knowledge, and ideas evolve and are increased and refined, the branches of philosophy in charge of describing them should also be increased and refined. In this work we try to expand some ideas as a response to the recent approach from several sciences to complex systems. Because of their novelty, some of these ideas might require further refinement and may seem unfinished, but we need to start with something. Only with their propagation and feedback from critics they might (...) be improved. We make a brief introduction to complex systems, for then defining abstraction levels. Abstraction levels represent simplicities and regularities in nature. We make an ontological distinction of absolute being and relative being, and then discuss issues on causality, metaphysics, and determinism. (shrink)

In this chapter we want to provide philosophical tools for understanding and reasoning about complex systems. Classical thinking, which is taught at most schools and universities, has several problems for coping with complexity. We review classical thinking and its drawbacks when dealing with complexity, for then presenting ways of thinking which allow the better understanding of complex systems. Examples illustrate the ideas presented. This chapter does not deal with specific tools and techniques for managing complex systems, but we try to (...) bring forth ideas that facilitate the thinking and speaking about complex systems. (shrink)

The present paper introduces "ontomimetic simulation" and argues that this class of models has enabled the investigation of hypotheses about complex systems in new ways that have epistemological relevance. Ontomimetic simulation can be differentiated from other types of modeling by its reliance on causal similarity in addition to representation. Phenomena are modeled not directly but via mimesis of the ontology (i.e. the "underlying physics", microlevel etc.) of systems and a subsequent animation of the resulting model ontology as a dynamical system. (...) While the ontology is clearly used for computing system states, what is epistemologically important is that it is viewed as a hypothesis about the makeup of the studied system. This type of simulation, where model ontologies are used as hypotheses, is here called inverse ontomimetic simulation since it reverses the typical informational path from the target to the model system. It links experimental and analytical techniques in being explicitly dynamical while at the same time capable of abstraction. Inverse ontomimetic simulation is argued to have a great impact on science and to be the tool for hypothesis-testing that has made systematic theory development for complex systems possible. (shrink)