Results for 'Information modeling'

991 found
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  1.  44
    Information modeling aspects of software development.Timothy R. Colburn - 1998 - Minds and Machines 8 (3):375-393.
    The distinction between the modeling of information and the modeling of data in the creation of automated systems has historically been important because the development tools available to programmers have been wedded to machine oriented data types and processes. However, advances in software engineering, particularly the move toward data abstraction in software design, allow activities reasonably described as information modeling to be performed in the software creation process. An examination of the evolution of programming languages (...)
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  2.  64
    Ontological aspects of information modeling.Robert L. Ashenhurst - 1996 - Minds and Machines 6 (3):287-394.
    Information modeling (also known as conceptual modeling or semantic data modeling) may be characterized as the formulation of a model in which information aspects of objective and subjective reality are presented (the application), independent of datasets and processes by which they may be realized (the system).A methodology for information modeling should incorporate a number of concepts which have appeared in the literature, but should also be formulated in terms of constructs which are understandable (...)
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  3. Information: From Philosophic to Physics Concepts for Informational Modeling of Consciousness.Florin Gaiseanu - 2018 - Philosophy Study 8 (8).
    Information was a frequently used concept in many fields of investigation. However, this concept is still not really understood, when it is referred for instance to consciousness and its informational structure. In this paper it is followed the concept of information from philosophical to physics perspective, showing especially how this concept could be extended to matter in general and to the living in particular, as a result of the intimate interaction between matter and information, the human body (...)
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  4.  18
    Informational Macrodynamics for Cognitive Information Modeling and Computation.Vladimir S. Lerner - 2001 - Journal of Intelligent Systems 11 (6):409-470.
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  5.  10
    Simulation and Architecture: Mapping Building Information Modeling.Nathalie Bredella - 2019 - NTM Zeitschrift für Geschichte der Wissenschaften, Technik und Medizin 27 (4):419-441.
    In the 1990s, Building Information Modeling (BIM) software significantly altered architectural approaches to planning and building. Based on parametric methods, BIM technologies sought to simulate the construction process prior to a building’s realisation. These computer simulations challenged the existing practice of representing a building through plan, section and elevation, proposing that one computational model could create a more efficient way of building. The history of BIM explorations and applications, while hardly linear, can be traced back to developments in (...)
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  6.  6
    Informational Structure of the Living Systems: From Philosophy to Informational Modeling.Florin Gaiseanu - 2020 - Philosophy Study 10 (12).
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  7. Modeling Information.Patrick Grim - 2016 - In Luciano Floridi (ed.), Routledge Handbook of Philosophy of Information. Routledge. pp. 137-152.
    The topics of modeling and information come together in at least two ways. Computational modeling and simulation play an increasingly important role in science, across disciplines from mathematics through physics to economics and political science. The philosophical questions at issue are questions as to what modeling and simulation are adding, altering, or amplifying in terms of scientific information. What changes with regard to information acquisition, theoretical development, or empirical confirmation with contemporary tools of computational (...)
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  8. Empirical Modeling and Information Semantics.Gordana Dodig-Crnkovic - 2008 - Mind and Society 7 (2):157.
    This paper investigates the relationship between reality and model, information and truth. It will argue that meaningful data need not be true in order to constitute information. Information to which truth-value cannot be ascribed, partially true information or even false information can lead to an interesting outcome such as technological innovation or scientific breakthrough. In the research process, during the transition between two theoretical frameworks, there is a dynamic mixture of old and new concepts in (...)
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  9. Modeling Partially Reliable Information Sources: A General Approach Based on Dempster-Shafer Theory.Stephan Hartmann & Rolf Haenni - 2006 - Information Fusion 7:361-379.
    Combining testimonial reports from independent and partially reliable information sources is an important epistemological problem of uncertain reasoning. Within the framework of Dempster–Shafer theory, we propose a general model of partially reliable sources, which includes several previously known results as special cases. The paper reproduces these results on the basis of a comprehensive model taxonomy. This gives a number of new insights and thereby contributes to a better understanding of this important application of reasoning with uncertain and incomplete (...). (shrink)
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  10. Understanding scientists' computational modeling decisions about climate risk management strategies using values-informed mental models.Lauren Mayer, Kathleen Loa, Bryan Cwik, Nancy Tuana, Klaus Keller, Chad Gonnerman, Andrew Parker & Robert Lempert - 2017 - Global Environmental Change 42:107-116.
    When developing computational models to analyze the tradeoffs between climate risk management strategies (i.e., mitigation, adaptation, or geoengineering), scientists make explicit and implicit decisions that are influenced by their beliefs, values and preferences. Model descriptions typically include only the explicit decisions and are silent on value judgments that may explain these decisions. Eliciting scientists’ mental models, a systematic approach to determining how they think about climate risk management, can help to gain a clearer understanding of their modeling decisions. In (...)
     
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  11. Modeling sequential information integration with parallel constraint satisfaction.Katja Mehlhorn & Georg Jahn - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society. pp. 2469--2474.
  12.  36
    Empirical modeling and information semantics.Gordana Dodig-Crnkovic - 2008 - Mind and Society 7 (2):157-166.
    This paper investigates the relationship between reality and model, information and truth. It will argue that meaningful data need not be true in order to constitute information. Information to which truth-value cannot be ascribed, partially true information or even false information can lead to an interesting outcome such as technological innovation or scientific breakthrough. In the research process, during the transition between two theoretical frameworks, there is a dynamic mixture of old and new concepts in (...)
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  13.  11
    Modeling information exchange opportunities for effective human–computer teamwork.Ece Kamar, Yaʼakov Gal & Barbara J. Grosz - 2013 - Artificial Intelligence 195 (C):528-550.
  14.  16
    Language modeling for information retrieval.Börkur Sigurbjörnsson - 2004 - Journal of Logic, Language and Information 13 (4):531-534.
  15.  47
    Information or logic in modeling conscious systems?Igor Aleksander, David Gamez & Helen Morton - 2009 - International Journal of Machine Consciousness 1 (2):185-192.
  16.  78
    Modeling information ethics: The joint moderating role of locus of control and job insecurity. [REVIEW]Chieh-Peng Lin & Cherng G. Ding - 2003 - Journal of Business Ethics 48 (4):335-346.
    Information unethical behavior is concerned with ethical behavioural conflicts in the use of information, information technologies, and information systems. This study examines the combination of locus of control and job insecurity as a joint moderator on the decision making process for information ethical behavioral intentions. A conceptual model is proposed to see the joint moderating role of LOC and JI. In the model, ethical behavioral intentions are influenced directly by ethical attitude, personal values, and perceived (...)
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  17.  11
    Continuous versus discrete information processing: Modeling accumulation of partial information.Roger Ratcliff - 1988 - Psychological Review 95 (2):238-255.
  18.  16
    Online Tourism Information and Tourist Behavior: A Structural Equation Modeling Analysis Based on a Self-Administered Survey.Salman Majeed, Zhimin Zhou, Changbao Lu & Haywantee Ramkissoon - 2020 - Frontiers in Psychology 11.
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  19. Economic and mathematical modeling of integration influence of information and communication technologies on the development of e-commerce of industrial enterprises.Igor Kryvovyazyuk, Igor Britchenko, Liubov Kovalska, Iryna Oleksandrenko, Liudmyla Pavliuk & Olena Zavadska - 2023 - Journal of Theoretical and Applied Information Technology 101 (11):3801-3815.
    This research aims at establishing the impact of information and communication technologies (ICT) on e-commerce development of industrial enterprises by means of economic and mathematical modelling. The goal was achieved using the following methods: theoretical generalization, analysis and synthesis (to critically analyse the scientific approaches of scientists regarding the expediency of using mathematical models in the context of enterprises’ e-commerce development), target, comparison and grouping (to reveal innovative methodological approach to assessing ICT impact on e-commerce development of industrial enterprises), (...)
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  20.  31
    Exploiting Multiple Sources of Information in Learning an Artificial Language: Human Data and Modeling.Pierre Perruchet & Barbara Tillmann - 2010 - Cognitive Science 34 (2):255-285.
    This study investigates the joint influences of three factors on the discovery of new word‐like units in a continuous artificial speech stream: the statistical structure of the ongoing input, the initial word‐likeness of parts of the speech flow, and the contextual information provided by the earlier emergence of other word‐like units. Results of an experiment conducted with adult participants show that these sources of information have strong and interactive influences on word discovery. The authors then examine the ability (...)
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  21.  48
    Cancer Modeling: the Advantages and Limitations of Multiple Perspectives.A. Plutynski - 2020 - In Michela Massimi & Casey D. McCoy (eds.), Understanding Perspectivism (Open Access): Scientific Challenges and Methodological Prospects. New York, NY, USA: Routledge.
    Cancer is a paradigmatic case of a complex causal process; causes of cancer operate at a variety of temporal and spatial scales, and the respects in which these causes act and interact are diverse. There are, for instance, temporal order effects, organizational effects, structural effects, and dynamic relationships between causes operating at different temporal and spatial scales. Because of this complexity, models of cancer initiation and progression often involve deliberate choices to focus on one time scale, one causal pathway, or (...)
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  22.  6
    Understanding Dynamics of Information Transmission in Drosophila melanogaster Using a Statistical Modeling Framework for Longitudinal Network Data.Cristian Pasquaretta, Elizabeth Klenschi, Jérôme Pansanel, Marine Battesti, Frederic Mery & Cédric Sueur - 2016 - Frontiers in Psychology 7.
  23.  14
    Linear Ballistic Accumulator Modeling of Attentional Bias Modification Revealed Disturbed Evidence Accumulation of Negative Information by Explicit Instruction.Yuki Nishiguchi, Jiro Sakamoto, Yoshihiko Kunisato & Keisuke Takano - 2019 - Frontiers in Psychology 10.
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  24.  8
    Spatial But Not Oculomotor Information Biases Perceptual Memory: Evidence From Face Perception and Cognitive Modeling.Andrea L. Wantz, Janek S. Lobmaier, Fred W. Mast & Walter Senn - 2017 - Cognitive Science 41 (6):1533-1554.
    Recent research put forward the hypothesis that eye movements are integrated in memory representations and are reactivated when later recalled. However, “looking back to nothing” during recall might be a consequence of spatial memory retrieval. Here, we aimed at distinguishing between the effect of spatial and oculomotor information on perceptual memory. Participants’ task was to judge whether a morph looked rather like the first or second previously presented face. Crucially, faces and morphs were presented in a way that the (...)
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  25.  29
    Short‐term information processing, long‐term responses: Insights by mathematical modeling of signal transduction.Annette Schneider, Ursula Klingmüller & Marcel Schilling - 2012 - Bioessays 34 (7):542-550.
  26.  17
    Dynamic programming, limited information and behavioral modeling.Bradley W. Dickinson - 1991 - Behavioral and Brain Sciences 14 (1):96-97.
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  27.  3
    Integration of intelligent information technologies ensembles for modeling and classification.Andrey Shabalov, Eugene Semenkin & Pavel Galushin - 2012 - In Emilio Corchado, Vaclav Snasel, Ajith Abraham, Michał Woźniak, Manuel Grana & Sung-Bae Cho (eds.), Hybrid Artificial Intelligent Systems. Springer. pp. 365--374.
  28. Optimality modeling and explanatory generality.Angela Potochnik - 2007 - Philosophy of Science 74 (5):680-691.
    The optimality approach to modeling natural selection has been criticized by many biologists and philosophers of biology. For instance, Lewontin (1979) argues that the optimality approach is a shortcut that will be replaced by models incorporating genetic information, if and when such models become available. In contrast, I think that optimality models have a permanent role in evolutionary study. I base my argument for this claim on what I think it takes to best explain an event. In certain (...)
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  29.  31
    Enterprise risk management: Applications of economic modeling and information technology.Christine P. Ries - 2001 - Mind and Society 2 (2):1-8.
    Factory floors throughout the global economy are rapidly transforming themselves into potentially fertile laboratories for research in the cognitive sciences. The information revolution has challenged our understanding of perception and cognition. Innovations in information technologies have also provided us with new methods and environments for the study of cognition. On the business and economic front, information technology is supporting the development of new corporate information systems-Enterprise Systems-that will revolutionize the decision-making, reporting and reward environments in corporations. (...)
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  30.  24
    Modeling the Structure and Dynamics of Semantic Processing.Armand S. Rotaru, Gabriella Vigliocco & Stefan L. Frank - 2018 - Cognitive Science 42 (8):2890-2917.
    The contents and structure of semantic memory have been the focus of much recent research, with major advances in the development of distributional models, which use word co‐occurrence information as a window into the semantics of language. In parallel, connectionist modeling has extended our knowledge of the processes engaged in semantic activation. However, these two lines of investigation have rarely been brought together. Here, we describe a processing model based on distributional semantics in which activation spreads throughout a (...)
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  31.  18
    Parameters, Predictions, and Evidence in Computational Modeling: A Statistical View Informed by ACT–R.Rhiannon Weaver - 2008 - Cognitive Science 32 (8):1349-1375.
    Model validation in computational cognitive psychology often relies on methods drawn from the testing of theories in experimental physics. However, applications of these methods to computational models in typical cognitive experiments can hide multiple, plausible sources of variation arising from human participants and from stochastic cognitive theories, encouraging a “model fixed, data variable” paradigm that makes it difficult to interpret model predictions and to account for individual differences. This article proposes a likelihood‐based, “data fixed, model variable” paradigm in which models (...)
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  32. The GRAIN model: A framework for modeling the dynamics of information processing.James L. McClelland - 1993 - In David E. Meyer & Sylvan Kornblum (eds.), Attention and Performance Xiv. MIT Press. pp. 655--688.
  33.  13
    Privacy, Deontic Epistemic Action Logic and Software Agents: An Executable Approach to Modeling Moral Constraints in Complex Informational Relationships.V. Wiegel, M. Hoven & G. Lokhorst - 2005 - Ethics and Information Technology 7 (4):251-264.
    In this paper we present an executable approach to model interactions between agents that involve sensitive, privacy-related information. The approach is formal and based on deontic, epistemic and action logic. It is conceptually related to the Belief-Desire-Intention model of Bratman. Our approach uses the concept of sphere as developed by Waltzer to capture the notion that information is provided mostly with restrictions regarding its application. We use software agent technology to create an executable approach. Our agents hold beliefs (...)
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  34.  43
    Modeling Self -Organization.Stanley N. Salthe - 1988 - Semiotics:14-23.
    Foremost among the tasks facing a semiotically-informed modeling of natural open systems is the recognition and representation of self-organization. This forces attention on process, time, and energetics to complement the conventional semiotic bias toward structure, space, and informatics. While self -organization might be captured in numerous operational idioms, we suggest that the fundamentally distinctive formal structures of (a) development (intrinsic predictability) and (b) evolution (unexpected change through change in contextual meaning) constitute thewarp and woof of virtually all observations on (...)
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  35.  21
    The face advantage in recalling episodic information: Implications for modeling human memory.Ljubica Damjanovic - 2011 - Consciousness and Cognition 20 (2):309-311.
    Recent evidence comparing recognition memory for famous faces and famous voices reveals an advantage for faces to elicit greater levels of episodic and semantic information than voices, even when overall levels of difficulty are matched between the two modalities. The paper by Barsics and Brédart makes a significant advance to this literature by demonstrating that even when encoding strategies are maximized to favor voice over face encoding by using personally familiar stimuli, facial cues continue to provide a more successful (...)
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  36.  26
    Student assessment of teaching as a source of information about aspects of teaching quality in multiple subject domains: an application of multilevel bifactor structural equation modeling.Ronny Scherer & Jan-Eric Gustafsson - 2015 - Frontiers in Psychology 6.
  37. Modeling Rational Players: Part I.Ken Binmore - 1987 - Economics and Philosophy 3 (2):179-214.
    Game theory has proved a useful tool in the study of simple economic models. However, numerous foundational issues remain unresolved. The situation is particularly confusing in respect of the non-cooperative analysis of games with some dynamic structure in which the choice of one move or another during the play of the game may convey valuable information to the other players. Without pausing for breath, it is easy to name at least 10 rival equilibrium notions for which a serious case (...)
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  38.  26
    Modeling Spatial Knowledge.Benjamin Kuipers - 1978 - Cognitive Science 2 (2):129-153.
    A person's cognitive map, or knowledge of large‐scale space, is built up from observations gathered as he travels through the environment. It acts as a problem solver to find routes and relative positions, as well as describing the current location. The TOUR model captures the multiple representations that make up the cognitive map, the problem‐solving strategies it uses, and the mechanisms for assimilating new information. The representations have rich collections of states of partial knowledge, which support many of the (...)
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  39.  30
    Online Social Network Emergency Public Event Information Propagation and Nonlinear Mathematical Modeling.Xiaoyang Liu, Chao Liu & Xiaoping Zeng - 2017 - Complexity:1-7.
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  40. Computational Modeling as a Philosophical Methodology.Patrick Grim - 2004 - In Luciano Floridi (ed.), The Blackwell Guide to the Philosophy of Computing and Information. Oxford, UK: Blackwell. pp. 337–349.
    Since the sixties, computational modeling has become increasingly important in both the physical and the social sciences, particularly in physics, theoretical biology, sociology, and economics. Sine the eighties, philosophers too have begun to apply computational modeling to questions in logic, epistemology, philosophy of science, philosophy of mind, philosophy of language, philosophy of biology, ethics, and social and political philosophy. This chapter analyzes a selection of interesting examples in some of those areas.
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  41.  37
    Modeling Lung Branching Morphogenesis.Takashi Miura - 2013 - Biological Theory 8 (3):265-273.
    Biological forms are very complex, and mechanisms of pattern formation are not well understood. Although developmental biology deals with the mechanistic explanation of patterns, currently we do not know how to understand the mechanisms of pattern formation from huge amounts of molecular information. In this article, I present one useful tool, mathematical modeling, to obtain a mechanistic understanding of biological pattern formation, and show an actual example in lung branching morphogenesis. In this example, mathematical modeling plays an (...)
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  42.  7
    Modeling Response Time and Responses in Multidimensional Health Measurement.Chun Wang, David J. Weiss & Shiyang Su - 2019 - Frontiers in Psychology 10.
    This study explored calibrating a large item bank for use in multidimensional health measurement with computerized adaptive testing, using both item responses and response time (RT) information. The Activity Measure for Post-Acute Care is a patient-reported outcomes measure comprised of three correlated scales (Applied Cognition, Daily Activities, and Mobility). All items from each scale are Likert type, so that a respondent chooses a response from an ordered set of four response options. The most appropriate item response theory model for (...)
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  43.  18
    Modeling Statistical Insensitivity: Sources of Suboptimal Behavior.Annie Gagliardi, Naomi H. Feldman & Jeffrey Lidz - 2016 - Cognitive Science 40 (7):188-217.
    Children acquiring languages with noun classes have ample statistical information available that characterizes the distribution of nouns into these classes, but their use of this information to classify novel nouns differs from the predictions made by an optimal Bayesian classifier. We use rational analysis to investigate the hypothesis that children are classifying nouns optimally with respect to a distribution that does not match the surface distribution of statistical features in their input. We propose three ways in which children's (...)
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  44.  23
    Modeling individual differences in working memory performance: a source activation account.Larry Z. Daily, Marsha C. Lovett & Lynne M. Reder - 2001 - Cognitive Science 25 (3):315-353.
    Working memory resources are needed for processing and maintenance of information during cognitive tasks. Many models have been developed to capture the effects of limited working memory resources on performance. However, most of these models do not account for the finding that different individuals show different sensitivities to working memory demands, and none of the models predicts individual subjects' patterns of performance. We propose a computational model that accounts for differences in working memory capacity in terms of a quantity (...)
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  45.  29
    Computer Modeling in Philosophy of Religion.F. LeRon Shults - 2019 - Open Philosophy 2 (1):108-125.
    How might philosophy of religion be impacted by developments in computational modeling and social simulation? After briefly describing some of the content and context biases that have shaped traditional philosophy of religion, this article provides examples of computational models that illustrate the explanatory power of conceptually clear and empirically validated causal architectures informed by the bio-cultural sciences. It also outlines some of the material implications of these developments for broader metaphysical and metaethical discussions in philosophy. Computer modeling and (...)
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  46. Modeling ancient and modern arithmetic practices: Addition and multiplication with Arabic and Roman numerals.Dirk Schlimm & Hansjörg Neth - 2008 - In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 2097--2102.
    To analyze the task of mental arithmetic with external representations in different number systems we model algorithms for addition and multiplication with Arabic and Roman numerals. This demonstrates that Roman numerals are not only informationally equivalent to Arabic ones but also computationally similar—a claim that is widely disputed. An analysis of our models' elementary processing steps reveals intricate tradeoffs between problem representation, algorithm, and interactive resources. Our simulations allow for a more nuanced view of the received wisdom on Roman numerals. (...)
     
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  47. Elman nets for credit risk management / G. di Tollo, M. Lyra ; Part IV: Modeling from physics: From chemical kinetics to models of acquisition of information: on the importance of the rate of acquisition of information.G. Monaco - 2010 - In Marisa Faggini, Concetto Paolo Vinci, Antonio Abatemarco, Rossella Aiello, F. T. Arecchi, Lucio Biggiero, Giovanna Bimonte, Sergio Bruno, Carl Chiarella, Maria Pia Di Gregorio, Giacomo Di Tollo, Simone Giansante, Jaime Gil Aluja, A. I͡U Khrennikov, Marianna Lyra, Riccardo Meucci, Guglielmo Monaco, Giancarlo Nota, Serena Sordi, Pietro Terna, Kumaraswamy Velupillai & Alessandro Vercelli (eds.), Decision Theory and Choices: A Complexity Approach. Springer Verlag Italia.
     
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  48.  45
    Multiscale Modeling of Gene–Behavior Associations in an Artificial Neural Network Model of Cognitive Development.Michael S. C. Thomas, Neil A. Forrester & Angelica Ronald - 2016 - Cognitive Science 40 (1):51-99.
    In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively common gene variants and individual differences in behavior. It is perhaps surprising that such associations can be detected despite the remoteness of these levels of description, and the fact that behavior is the outcome of an extended developmental process involving interaction of the whole organism with a variable environment. Given (...)
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  49.  22
    Two types of potential functions and their use in the modeling of information: two applications from the social sciences.Emmanuel E. Haven - 2015 - Frontiers in Psychology 6.
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  50.  34
    Analysis, modeling, and the management of international negotiations.Dhanesh K. Samarasan - 1993 - Theory and Decision 34 (3):275-291.
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