Results for 'Baldwin Effect, Emergence, Self-learning, Neural Networks'

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  1. Evolving Self-Taught Neural Networks: The Baldwin Effect and the Emergence of Intelligence.Nam Le - 2019 - In AISB Annual Convention 2019 -- 10th Symposium on AI & Games.
    The so-called Baldwin Effect generally says how learning, as a form of ontogenetic adaptation, can influence the process of phylogenetic adaptation, or evolution. This idea has also been taken into computation in which evolution and learning are used as computational metaphors, including evolving neural networks. This paper presents a technique called evolving self-taught neural networksneural networks that can teach themselves without external supervision or reward. The self-taught neural network is intrinsically (...)
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  2.  58
    Book Review of "The Embodied Mind: Cognitive Science and Human Experience". [REVIEW]Anand Rangarajan - manuscript
    This is an in-depth review of "The Embodied Mind: Cognitive Science and Human Experience" by Francisco Varela, Evan Thompson and Eleanor Rosch.
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  3. The Trans-Species Core SELF: The Emergence of Active Cultural and Neuro-Ecological Agents Through Self-Related Processing Within Subcortical-Cortical Midline Networks.Jaak Panksepp & Georg Northoff - 2009 - Consciousness and Cognition 18 (1):193–215.
    The nature of “the self” has been one of the central problems in philosophy and more recently in neuroscience. This raises various questions: Can we attribute a self to animals? Do animals and humans share certain aspects of their core selves, yielding a trans-species concept of self? What are the neural processes that underlie a possible trans-species concept of self? What are the developmental aspects and do they result in various levels of self-representation? Drawing on recent literature from both (...)
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  4. The Burqa Ban: Legal Precursors for Denmark, American Experiences and Experiments, and Philosophical and Critical Examinations.Ryan Long, Erik Baldwin, Anja Matwijkiw, Bronik Matwijkiw, Anna Oriolo & Willie Mack - 2018 - International Studies Journal 15 (1):157-206.
    As the title of the article suggests, “The Burqa Ban”: Legal Precursors for Denmark, American Experiences and Experiments, and Philosophical and Critical Examinations, the authors embark on a factually investigative as well as a reflective response. More precisely, they use The 2018 Danish “Burqa Ban”: Joining a European Trend and Sending a National Message (published as a concurrent but separate article in this issue of INTERNATIONAL STUDIES JOURNAL) as a platform for further analysis and discussion of different perspectives. These include (...)
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  5. Self-Assembling Networks.Jeffrey A. Barrett, Brian Skyrms & Aydin Mohseni - 2019 - British Journal for the Philosophy of Science 70 (1):1-25.
    We consider how an epistemic network might self-assemble from the ritualization of the individual decisions of simple heterogeneous agents. In such evolved social networks, inquirers may be significantly more successful than they could be investigating nature on their own. The evolved network may also dramatically lower the epistemic risk faced by even the most talented inquirers. We consider networks that self-assemble in the context of both perfect and imperfect communication and compare the behaviour of inquirers in each. This (...)
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  6. Networks of Gene Regulation, Neural Development and the Evolution of General Capabilities, Such as Human Empathy.Alfred Gierer - 1998 - Zeitschrift Für Naturforschung C - A Journal of Bioscience 53:716-722.
    A network of gene regulation organized in a hierarchical and combinatorial manner is crucially involved in the development of the neural network, and has to be considered one of the main substrates of genetic change in its evolution. Though qualitative features may emerge by way of the accumulation of rather unspecific quantitative changes, it is reasonable to assume that at least in some cases specific combinations of regulatory parts of the genome initiated new directions of evolution, leading to novel (...)
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  7.  99
    AISC 17 Talk: The Explanatory Problems of Deep Learning in Artificial Intelligence and Computational Cognitive Science: Two Possible Research Agendas.Antonio Lieto - 2018 - In Proceedings of AISC 2017.
    Endowing artificial systems with explanatory capacities about the reasons guiding their decisions, represents a crucial challenge and research objective in the current fields of Artificial Intelligence (AI) and Computational Cognitive Science [Langley et al., 2017]. Current mainstream AI systems, in fact, despite the enormous progresses reached in specific tasks, mostly fail to provide a transparent account of the reasons determining their behavior (both in cases of a successful or unsuccessful output). This is due to the fact that the classical problem (...)
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  8. Are Self-Organizing Biochemical Networks Emergent?Christophe Malaterre - 2009 - In Maryvonne Gérin & Marie-Christine Maurel (eds.), Origins of Life: Self-Organization and/or Biological Evolution? EDP Sciences. pp. 117--123.
    Biochemical networks are often called upon to illustrate emergent properties of living systems. In this contribution, I question such emergentist claims by means of theoretical work on genetic regulatory models and random Boolean networks. If the existence of a critical connectivity Kc of such networks has often been coined “emergent” or “irreducible”, I propose on the contrary that the existence of a critical connectivity Kc is indeed mathematically explainable in network theory. This conclusion also applies to many (...)
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  9. Empiricism Without Magic: Transformational Abstraction in Deep Convolutional Neural Networks.Cameron Buckner - 2018 - Synthese (12):1-34.
    In artificial intelligence, recent research has demonstrated the remarkable potential of Deep Convolutional Neural Networks (DCNNs), which seem to exceed state-of-the-art performance in new domains weekly, especially on the sorts of very difficult perceptual discrimination tasks that skeptics thought would remain beyond the reach of artificial intelligence. However, it has proven difficult to explain why DCNNs perform so well. In philosophy of mind, empiricists have long suggested that complex cognition is based on information derived from sensory experience, often (...)
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  10. Triggering Individual Emergence: Inspiration of Banathy, the Visionary.Gordon Dyer - 2002 - World Futures 58 (5 & 6):365 – 378.
    This paper examines how metaphors can play a key role in triggering individual emergence. Metaphor is referenced in two main ways: the enthalpy metaphor is used to provide understanding of, and guide, the process of effective conversation. Metaphor is also interpreted very broadly to define those images, analogies, concepts, models, and theories that define our understanding of the world and our perception. It is our perception that must change if we are to improve the future. The paper examines how sharing (...)
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  11. Psychological Altruism Vs. Biological Altruism: Narrowing the Gap with the Baldwin Effect.Mahesh Ananth - 2005 - Acta Biotheoretica 53 (3):217-239.
    This paper defends the position that the supposed gap between biological altruism and psychological altruism is not nearly as wide as some scholars (e.g., Elliott Sober) insist. Crucial to this defense is the use of James Mark Baldwin's concepts of “organic selection”and “social heredity” to assist in revealing that the gap between biological and psychological altruism is more of a small lacuna. Specifically, this paper argues that ontogenetic behavioral adjustments, which are crucial to individual survival and reproduction, are also (...)
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  12. Predicting Books’ Overall Rating Using Artificial Neural Network.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Engineering Research (IJAER) 3 (8):11-17.
    We developed an Artificial Neural Network (ANN) model for predicting the overall rating of books. The prediction is based on some Factors (bookID, title, authors, isbn, language_code, isbn13, # num_pages, ratings_count, text_reviews_count), which used as input variables and (average_rating) as output for our ANN predictive model. Our model established, trained, and validated using data set, which its title is “Goodreads-books”. Model evaluation showed that the ANN model is able to predict correctly 99.90% of the validation instances.
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  13. Symbols Are Not Uniquely Human.Sidarta Ribeiro, Angelo Loula, Ivan Araújo, Ricardo Gudwin & Joao Queiroz - 2006 - Biosystems 90 (1):263-272.
    Modern semiotics is a branch of logics that formally defines symbol-based communication. In recent years, the semiotic classification of signs has been invoked to support the notion that symbols are uniquely human. Here we show that alarm-calls such as those used by African vervet monkeys (Cercopithecus aethiops), logically satisfy the semiotic definition of symbol. We also show that the acquisition of vocal symbols in vervet monkeys can be successfully simulated by a computer program based on minimal semiotic and neurobiological constraints. (...)
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  14. What Does It Mean to Understand? Neural Networks Case.Albert Ierusalem & Aleksandr Senin - manuscript
    We can say that we understand neural networks then and only then if you will come to me and say that the best model ever for some task has a 100 layers, and I will answer "No! 101 layers model is the best!".
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  15. Organic Selection and Social Heredity: The Original Baldwin Effect Revisited.Nam Le - 2019 - Artificial Life Conference Proceedings 2019 (31):515-522.
    The so-called “Baldwin Effect” has been studied for years in the fields of Artificial Life, Cognitive Science, and Evolutionary Theory across disciplines. This idea is often conflated with genetic assimilation, and has raised controversy in trans-disciplinary scientific discourse due to the many interpretations it has. This paper revisits the “Baldwin Effect” in Baldwin’s original spirit from a joint historical, theoretical and experimental approach. Social Heredity – the inheritance of cultural knowledge via non-genetic means in Baldwin’s term (...)
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  16. Cognitive Penetration, Perceptual Learning and Neural Plasticity.Ariel S. Cecchi - 2014 - Dialectica 68 (1):63-95.
    Cognitive penetration of perception, broadly understood, is the influence that the cognitive system has on a perceptual system. The paper shows a form of cognitive penetration in the visual system which I call ‘architectural’. Architectural cognitive penetration is the process whereby the behaviour or the structure of the perceptual system is influenced by the cognitive system, which consequently may have an impact on the content of the perceptual experience. I scrutinize a study in perceptual learning that provides empirical evidence that (...)
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  17. Self-Organization, Emergence, and Constraint in Complex Natural Systems.Jon Lawhead - manuscript
    Contemporary complexity theory has been instrumental in providing novel rigorous definitions for some classic philosophical concepts, including emergence. In an attempt to provide an account of emergence that is consistent with complexity and dynamical systems theory, several authors have turned to the notion of constraints on state transitions. Drawing on complexity theory directly, this paper builds on those accounts, further developing the constraint-based interpretation of emergence and arguing that such accounts recover many of the features of more traditional accounts. We (...)
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  18. Learning Networks and Connective Knowledge.Stephen Downes - 2010 - In Harrison Hao Yang & Steve Chi-Yin Yuen (eds.), Collective Intelligence and E-Learning 2.0: Implications of Web-Based Communities and Networking. IGI Global.
    The purpose of this chapter is to outline some of the thinking behind new e-learning technology, including e-portfolios and personal learning environments. Part of this thinking is centered around the theory of connectivism, which asserts that knowledge - and therefore the learning of knowledge - is distributive, that is, not located in any given place (and therefore not 'transferred' or 'transacted' per se) but rather consists of the network of connections formed from experience and interactions with a knowing community. And (...)
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  19.  83
    Predicting Whether a Couple is Going to Get Divorced or Not Using Artificial Neural Networks.Ibrahim M. Nasser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (10):49-55.
    In this paper, an artificial neural network (ANN) model was developed and validated to predict whether a couple is going to get divorced or not. Prediction is done based on some questions that the couple answered, answers of those questions were used as the input to the ANN. The model went through multiple learning-validation cycles until it got 100% accuracy.
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  20.  73
    Perceptual Learning, the Mere Exposure Effect and Aesthetic Antirealism.Bence Nanay - 2017 - Leonardo 50:58-63.
    It has been argued that some recent experimental findings about the mere exposure effect can be used to argue for aesthetic antirealism: the view that there is no fact of the matter about aesthetic value. The aim of this paper is to assess this argument and point out that this strategy, as it stands, does not work. But we may still be able to use experimental findings about the mere exposure effect in order to engage with the aesthetic realism/antirealism debate. (...)
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  21.  20
    The 'Hard Problem' of Phenomenal Perception.Dieter Wandschneider - 2015 - Zeitschrift für Philosophische Forschung 69:550–568.
    The center of this investigation is the hard problem of phenomenal perception. To be clear, hereby it is thought of higher animals; accordingly the problem of Human consciousness will explicitly not be treated. The so-called explanatory gap (Levine), i.e. missing a neural explanation of experiences, here is emergence-theoretically countered: It is argued that systems own properties and laws different from those of their components. Applied to the brain the phenomenal character of perception is explained as an emergence effect from (...)
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  22. Knowledge Bases and Neural Network Synthesis.Todd R. Davies - 1991 - In Hozumi Tanaka (ed.), Artificial Intelligence in the Pacific Rim: Proceedings of the Pacific Rim International Conference on Artificial Intelligence. IOS Press. pp. 717-722.
    We describe and try to motivate our project to build systems using both a knowledge based and a neural network approach. These two approaches are used at different stages in the solution of a problem, instead of using knowledge bases exclusively on some problems, and neural nets exclusively on others. The knowledge base (KB) is defined first in a declarative, symbolic language that is easy to use. It is then compiled into an efficient neural network (NN) representation, (...)
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  23. Images and Constructs: Can the Neural Correlates of Self Be Revealed Through Radiological Analysis?Stan Klein - 2013 - International Journal of Psychological Research 6:117-132.
    In this paper I argue that radiological attempts to elucidate the properties of self -- an endeavor currently popular in the social neurosciences -- are fraught with conceptual difficulties. I first discuss several philosophical criteria that increase the chances we are posing the “right” questions to nature. I then discuss whether these criteria are met when empirical efforts are directed at one of the central constructs in the social sciences – the human self. In particular, I consider whether recent attempts (...)
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  24. Understanding From Machine Learning Models.Emily Sullivan - forthcoming - British Journal for the Philosophy of Science:axz035.
    Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide understanding misguided? In (...)
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  25.  37
    Artificial Neural Network for Predicting Workplace Absenteeism.Raghad Adnan Abu Hassanein, Saja Ahmed Al-Qassas, Fatima Naji Abu Tir & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 4 (9):62-67.
    Associations can grow, succeed, and sustain if their employees are committed. The main assets of an association are those employees who are giving it a required number of hours per month, in other words, those employees who are punctual towards their attendance. Absenteeism from work is a multibillion-dollar problem, and it costs money and decreases revenue. At the time of hiring an employee, Associations do not have an objective mechanism to predict whether an employee will be punctual towards attendance or (...)
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  26. Revelation and Artificial Neural Networks.Lascelles G. B. James - manuscript
    The grammatical forms and material of the book of Revelation suggest a complex interplay of Old Testament and 1st century literature and language. As well, the book does not lack its own peculiarity and character that is unparalleled in the literate world. Various analytical tools including historical-comparative methodologies have been employed to reconstruct the linguistic paradigm of the book. Artificial intelligence and its derivatives provide alternate methods of probing this paradigm.
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  27. Scientism, Philosophy and Brain-Based Learning.Gregory M. Nixon - 2013 - Northwest Journal of Teacher Education 11 (1):113-144.
    [This is an edited and improved version of "You Are Not Your Brain: Against 'Teaching to the Brain'" previously published in *Review of Higher Education and Self-Learning* 5(15), Summer 2012.] Since educators are always looking for ways to improve their practice, and since empirical science is now accepted in our worldview as the final arbiter of truth, it is no surprise they have been lured toward cognitive neuroscience in hopes that discovering how the brain learns will provide a nutshell explanation (...)
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  28. Kizel, A. (2016). “Philosophy with Children as an Educational Platform for Self-Determined Learning”. Cogent Education, Vol. 3, Number 1: 1244026.Arie Kizel - 2016 - Cogent Education 3 (1):1244026.
    This article develops a theoretical framework for understanding the applicability and relevance of Philosophy with Children in and out of schools as a platform for self-determined learning in light of the developments of the past 40 years. Based on the philosophical writings of Matthew Lipman, the father of Philosophy for Children, and in particular his ideas regarding the search for meaning, it frames Philosophy with Children in six dimensions that contrast with classic classroom disciplinary learning, advocating a “pedagogy of searching” (...)
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  29. Self-Locating Belief and Updating on Learning.Darren Bradley - 2020 - Mind 129 (514):579-584.
    Self-locating beliefs cause a problem for conditionalization. Miriam Schoenfield offers a solution: that on learning E, agents should update on the fact that they learned E. However, Schoenfield is not explicit about whether the fact that they learned E is self-locating. I will argue that if the fact that they learned E is self-locating then the original problem has not been addressed, and if the fact that they learned E is not self-locating then the theory generates implausible verdicts which Schoenfield (...)
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  30. The Civilization at a Crossroads: Constructing the Paradigm Shift.Gennady Shkliarevsky - 2017 - Raleigh, NC: Glasstree Publishing.
    The book addresses the broad issue of sustainability of our civilization and seeks to contribute to the ongoing discussion of what many see as its systemic crisis. There is a broad agreement that new creative ideas, initiatives, and solutions are essential for dealing with the current problems. However, despite this recognition, we still know very little about the process of creation and how it works. As a result, our civilization fails to harness the enormous creative potential of humanity. This failure, (...)
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  31.  42
    ANN for Predicting the Effect of Oxygen Consumption of Thylakoid Membranes (Chloroplasts) From Spinach After Inhibition.Shawah Mohammad - 2020 - International Journal of Academic Engineering Research (IJAER) 3 (2):15-19.
    In this research, an Artificial Neural Network (ANN) model was developed and tested to predict effect of oxygen consumption of thylakoid membranes (chloroplasts) from spinach after inhibition. A number of factors were identified that may affect of oxygen consumption of thylakoid membranes from spinach. Factors such as curve, herbicide, dose, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using the data from some inhibition of photosynthesis in farms. (...)
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  32.  60
    How a Neural Net Grows Symbols.James Franklin - 1996 - In Peter Bartlett (ed.), Proceedings of the Seventh Australian Conference on Neural Networks, Canberra. Canberra, Australia: ACNN '96. pp. 91-96.
    Brains, unlike artificial neural nets, use symbols to summarise and reason about perceptual input. But unlike symbolic AI, they “ground” the symbols in the data: the symbols have meaning in terms of data, not just meaning imposed by the outside user. If neural nets could be made to grow their own symbols in the way that brains do, there would be a good prospect of combining neural networks and symbolic AI, in such a way as to (...)
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  33.  7
    Classification of Animal Species Using Neural Network.Rand Suhail Abu Al-Araj, Shaima Khalil Abed, Ahmed Nabil Al-Ghoul & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 4 (10):23-31.
    Abstract: Over 1.5 million living animal species have been described—of which around 1 million are insects—but it has been estimated there are over 7 million animal species in total. Animals range in length from 8.5 micrometres to 33.6 metres. In this paper an Artificial Neural Network (ANN) model, was developed and tested to predict animal species. There are a number of features that influence the classification of animal species. Such as the existence of hair/ feather, if the animal gives (...)
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  34. Neural Correlates of Error-Related Learning Deficits in Individuals with Psychopathy.A. K. L. von Borries, Inti A. Brazil, B. H. Bulten, J. K. Buitelaar, R. J. Verkes & E. R. A. de Bruijn - 2010 - Psychological Medicine 40:1559–1568.
    The results are interpreted in terms of a deficit in initial rule learning and subsequent generalization of these rules to new stimuli. Negative feedback is adequately processed at a neural level but this information is not used to improve behaviour on subsequent trials. As learning is degraded, the process of error detection at the moment of the actual response is diminished. Therefore, the current study demonstrates that disturbed error-monitoring processes play a central role in the often reported learning deficits (...)
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  35. Self and Others in Team-Based Learning: Acquiring Teamwork Skills for Business.Michela Betta - 2015 - Journal of Education for Business:1-6.
    Team-based learning (TBL) was applied within a third-year unit of study about ethics and management with the aim of enhancing students’ teamwork skills. A survey used to collect students’ opinions about their experience with TBL provided insights about how TBL helped students to develop an appreciation for teamwork and team collaboration. The team skills acquired through TBL could strengthen job readiness for business.
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  36. Learning, Institutions, and Economic Performance.C. Mantzavinos - 2004 - Perspectives on Politics 2:75-84.
    In this article, we provide a broad overview of the interplay among cognition, belief systems, and institutions, and how they affect economic performance. We argue that a deeper understanding of institutions’ emergence, their working properties, and their effect on economic and political outcomes should begin from an analysis of cognitive processes. We explore the nature of individual and collective learning, stressing that the issue is not whether agents are perfectly or boundedly rational, but rather how human beings actually reason and (...)
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  37. The Transition to Experiencing: II. The Evolution of Associative Learning Based on Feelings.Simona Ginsburg & Eva Jablonka - 2007 - Biological Theory 2 (3):231-243.
    We discuss the evolutionary transition from animals with limited experiencing to animals with unlimited experiencing and basic consciousness. This transition was, we suggest, intimately linked with the evolution of associative learning and with flexible reward systems based on, and modifiable by, learning. During associative learning, new pathways relating stimuli and effects are formed within a highly integrated and continuously active nervous system. We argue that the memory traces left by such new stimulus-effect relations form dynamic, flexible, and varied global sensory (...)
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  38. THE THEORY OF EVOLUTION: from the space vacuum to neural networks and moving forward.Oleg Bazaluk - 2014 - ISPC.
    In the book, the author defines the evolution as a continuous and nonlinear complex of the structure of matter, interaction types and environments of existence; analyzes existing in modern science and philosophy approaches to the study of the process of evolution, degree of development factors and causes of evolution. Unifying interdisciplinary research in cosmology, evolution, biology, neuroscience and philosophy, the author presents his vision of the evolution model of «Evolving matter», which allows us to consider not only the laws of (...)
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  39.  50
    Semantic Information G Theory and Logical Bayesian Inference for Machine Learning.Chenguang Lu - 2019 - Information 10 (8):261.
    An important problem with machine learning is that when label number n>2, it is very difficult to construct and optimize a group of learning functions, and we wish that optimized learning functions are still useful when prior distribution P(x) (where x is an instance) is changed. To resolve this problem, the semantic information G theory, Logical Bayesian Inference (LBI), and a group of Channel Matching (CM) algorithms together form a systematic solution. MultilabelMultilabel A semantic channel in the G theory consists (...)
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  40. Bayesvl: Visually Learning the Graphical Structure of Bayesian Networks and Performing MCMC with 'Stan'.Quan-Hoang Vuong & Viet-Phuong La - 2019 - Open Science Framework 2019:01-47.
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  41.  19
    Evaluation of The Impact Brought By Social Networks on Academic Performance of Higher Learning Students A Case of State University of Zanzibar (Suza).Othman Mohammed Ahmed & Lusekelo Kibona - 2018 - International Journal of Academic Management Science Research (IJAMSR) 2 (3):14-24.
    Abstract: Social networking sites and applications play an important role in the present generation or in today’s society in terms of communications and learning environment to some extent in which now educators or teachers are finding the way on how can these social networks be used as teaching and learning tools. Even though they have simplified communications among students and teachers they have also brought some impact to students in academic performance. The aim of this study was to explore (...)
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  42.  89
    Is There a Pro-Self Component Behind the Prominence Effect?Marcus Selart & Daniel Eek - 2005 - International Journal of Psychology 40:429-440.
    An important problem for decision-makers in society deals with the efficient and equitable allocation of scarce resources to individuals and groups. The significance of this problem is rapidly growing since there is a rising demand for scarce resources all over the world. Such resource dilemmas belong to a conceptually broader class of situations known as social dilemmas. In this type of dilemma, individual choices that appear ‘‘rational’’ often result in suboptimal group outcomes. In this article we study how people make (...)
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  43. Meaning Generation and Self-Consciousness: Neurophilosophical Applications of an Evolutionary Scenario? (Lomonosov Moscow State University. 2015 Presentation).Christophe Menant - manuscript
    The nature of human mind has been an open question for more than 2000 years and it is still today a mystery. There has been during the last 30 years a renewed interest from science and philosophy on that subject. Among the existing research domains is neurophilosophy, an interdisciplinary study of neuroscience and philosophy looking at neuronal aspects of access consciousness, of phenomenal consciousness and at functional aspects of consciousness. We propose here to look if self-consciousness could have a place (...)
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  44. Preliminary Considerations on a Possible Quantum Model of Consciousness Interfaced with a Non Lipschitz Chaotic Dynamics of Neural Activity.Elio Conte - 2012 - Journal of Consciousness Exploration and Research 3 (10):905-921.
    A model of consciousness and conscious experience is introduced. Starting with a non-Lipschitz Chaotic dynamics of neural activity, we propose that the synaptic transmission between adjacent as well as distant neurons should be regulated in brain dynamics through quantum tunneling. Further, based on various studies of different previous authors, we consider the emergence of very large quantum mechanical system representable by an abstract quantum net entirely based on quantum-like entities having in particular the important feature of expressing self-reference similar (...)
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  45.  14
    ITS for Learning Computer Networks.Monnes Hanjory & Mohammed Z. Shath - 2017 - International Journal of Advanced Research and Development 2 (1):74-78.
    Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation (...)
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  46. Self-Transcendence Correlates with Brain Function Impairment.Bernardo Kastrup - 2017 - Journal of Cognition and Neuroethics 4 (3):33-42.
    A broad pattern of correlations between mechanisms of brain function impairment and self-transcendence is shown. The pattern includes such mechanisms as cerebral hypoxia, physiological stress, transcranial magnetic stimulation, trance-induced physiological effects, the action of psychoactive substances and even physical trauma to the brain. In all these cases, subjects report self-transcending experiences o en described as ‘mystical’ and ‘awareness-expanding,’ as well as self-transcending skills o en described as ‘savant.’ The idea that these correlations could be rather trivially accounted for on the (...)
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  47. NEW PRINCIPLE FOR ENCODING INFORMATION TO CREATE SUBJECTIVE REALITY IN ARTIFICIAL NEURAL NETWORKS.Alexey Bakhirev - manuscript
    The paper outlines an analysis of two types of information - ordinary and subjective, consideration is given to the difference between the concepts of intelligence and perceiving mind. It also provides description of some logical functional features of consciousness. A technical approach is proposed to technical obtaining of subjective information by changing the signal’s time degree of freedom to the spatial one in order to obtain the "observer" function in the system and information signals appearing in relation to it, that (...)
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  48.  45
    Farewell to Chalmers' Zombie - The 'Principle Self-Preservation' as the Basis of 'Sense'.Dieter Wandschneider - 2018 - Zeitschrift für Philosophische Forschung 72:246-262.
    My argument is that Chalmers' zombie fiction and his rigid-designator-argument going back on Kripke comes down to a petitio principii. Rather, at the core it appears to be more related to the essential 'privacy' of the phenomenal internal perspective. In return for Chalmers I argue that the 'principle self-preservation' of living organisms necessarily implies subjectivity and the emergence of sense. The comparison with a robot proves instructive. The mode of 'mere physical' being is transcended if, in the form of phenomenal (...)
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  49. Wisdom of the Crowds Vs. Groupthink: Learning in Groups and in Isolation.Conor Mayo-Wilson, Kevin Zollman & David Danks - 2013 - International Journal of Game Theory 42 (3):695-723.
    We evaluate the asymptotic performance of boundedly-rational strategies in multi-armed bandit problems, where performance is measured in terms of the tendency (in the limit) to play optimal actions in either (i) isolation or (ii) networks of other learners. We show that, for many strategies commonly employed in economics, psychology, and machine learning, performance in isolation and performance in networks are essentially unrelated. Our results suggest that the appropriateness of various, common boundedly-rational strategies depends crucially upon the social context (...)
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  50.  31
    Lernen, Institutionen und Wirtschaftsleistung.C. Mantzavinos, Douglass C. North & Syed Shariq - 2005 - Analyse & Kritik 27 (2):320-337.
    This article provides a broad overview of the interplay among cognition, belief systems and institutions, fleshing out a position best characterized as 'cognitive institutionalism'. We argue that a deeper understanding of institutions, emergence, their working properties and their effect on economic performance should start with the analysis of cognitive processes. Exploring the nature of individual and collective learning the article suggests that the issue is not whether agents are perfectly or boundedly rational, but rather how human beings actually reason and (...)
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