Search results for 'evolutionary dynamics' (try it on Scholar)

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  1. Simon M. Huttegger, Brian Skyrms, Rory Smead & Kevin J. S. Zollman (2010). Evolutionary Dynamics of Lewis Signaling Games: Signaling Systems Vs. Partial Pooling. [REVIEW] Synthese 172 (1):177 - 191.score: 192.0
    Transfer of information between senders and receivers, of one kind or another, is essential to all life. David Lewis introduced a game theoretic model of the simplest case, where one sender and one receiver have pure common interest. How hard or easy is it for evolution to achieve information transfer in Lewis signaling?. The answers involve surprising subtleties. We discuss some if these in terms of evolutionary dynamics in both finite and infinite populations, with and without mutation.
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  2. M. Huttegger Simon, Rory Smead Brian Skyrms & J. S. Zollman Kevin (2010). Evolutionary Dynamics of Lewis Signaling Games: Signaling Systems Vs. Partial Pooling. Synthese 172 (1).score: 180.0
    Transfer of information between senders and receivers, of one kind or another, is essential to all life. David Lewis introduced a game theoretic model of the simplest case, where one sender and one receiver have pure common interest. How hard or easy is it for evolution to achieve information transfer in Lewis signaling?. The answers involve surprising subtleties. We discuss some if these in terms of evolutionary dynamics in both finite and infinite populations, with and without mutation.
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  3. Francisco Franchetti & William H. Sandholm (2013). An Introduction to Dynamo: Diagrams for Evolutionary Game Dynamics. [REVIEW] Biological Theory 8 (2):167-178.score: 168.0
    Dynamo: Diagrams for Evolutionary Game Dynamics is free, open-source software used to create phase diagrams and other images related to dynamical systems from evolutionary game theory. We describe how to use the software’s default settings to generate phase diagrams quickly and easily. We then explain how to take advantage of the software’s intermediate and advanced features to create diagrams that highlight the key properties of the dynamical system under study. Sample code and output are provided to help (...)
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  4. Robert A. Skipper Jr (2006). Stochastic Evolutionary Dynamics: Drift Versus Draft. Philosophy of Science 73 (5):655-665.score: 156.0
    In a small handful of papers in theoretical population genetics, John Gillespie (2000a, 2000b, 2001) argues that a new stochastic process he calls "genetic draft" is evolutionarily more significant than genetic drift. This case study of chance in evolution explores Gillespie's proposed stochastic evolutionary force and sketches the implications of Gillespie's argument for philosophers' explorations of genetic drift.
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  5. Robert Skipper (2006). Stochastic Evolutionary Dynamics: Drift Versus Draft. Philosophy of Science 73 (5):655-665.score: 156.0
    In a small handful of papers in theoretical population genetics, John Gillespie argues that a new stochastic process he calls "genetic draft" is evolutionarily more significant than genetic drift. This case study of chance in evolution explores Gillespie's proposed stochastic evolutionary force and sketches the implications of Gillespie's argument for philosophers' explorations of genetic drift.
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  6. William H. Sandholm (2010). Population Games and Evolutionary Dynamics. The Mit Press.score: 156.0
    A systematic, rigorous, comprehensive, and unified overview of evolutionary game theory.
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  7. Michael Doebeli (2012). Adaptive Dynamics: A Framework for Modeling the Long-Term Evolutionary Dynamics of Quantitative Traits. In E. Svensson & R. Calsbeek (eds.), The Adaptive Landscape in Evolutionary Biology. Oup Oxford. 227.score: 156.0
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  8. Rob Boyd, Evolutionary Dynamics of the Continuous Iterated Prisoner's Dilemma.score: 150.0
    The iterated prisoner’s dilemma (IPD) has been widely used in the biological and social sciences to model dyadic cooperation. While most of this work has focused on the discrete prisoner’s dilemma, in which actors choose between cooperation and defection, there has been some analysis of the continuous IPD, in which actors can choose any level of cooperation from zero to one. Here, we analyse a model of the continuous IPD with a limited strategy set, and show that a generous strategy (...)
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  9. J. McKenzie Alexander, Marc Ebner & Richard Watson, Co-Evolutionary Dynamics on a Deformable Landscape.score: 150.0
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  10. John Maynard Smith, Edward J. Feil & Noel H. Smith (2000). Population Structure and Evolutionary Dynamics of Pathogenic Bacteria. Bioessays 22 (12):1115-1122.score: 150.0
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  11. Erwin Diener (1988). C. Dyke, Evolutionary Dynamics of Complex Systems: A Study in Biosocial Complexity Reviewed By. Philosophy in Review 8 (12):477-480.score: 150.0
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  12. Don Ross (2007). Game Theory as Mathematics for Biology: Evolutionary Dynamics and Extensive Form Games Ross Cressman Cambridge, MA: MIT Press, 2003 (330 Pp; $48.00 Hbk; ISBN 0262033054); Moral Sentiments and Material Interests Herbert Gintis , Samuel Bowles , Robert Boyd and Ernst Fehr , Eds Cambridge, MA: MIT Press, 2005 (416 Pp; $50.00 Hbk; ISBN 0262072521). [REVIEW] Biological Theory 2 (1):104-107.score: 150.0
  13. Ruud Koopmans (2004). Movements and Media: Selection Processes and Evolutionary Dynamics in the Public Sphere. Theory and Society 33 (3/4):367-391.score: 150.0
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  14. S. Balaji & L. Aravind (2007). The Two Faces of Short‐Range Evolutionary Dynamics of Regulatory Modes in Bacterial Transcriptional Regulatory Networks. Bioessays 29 (7):625-629.score: 150.0
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  15. Philip V. Fellman, Roxana Wright & Justus Oguntuase (forthcoming). The Evolutionary Dynamics of Technology Replacement. Complexity.score: 150.0
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  16. C. Kello (2004). Characterizing the Evolutionary Dynamics of Language. Trends in Cognitive Sciences 8 (9):392-394.score: 150.0
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  17. Martin Lockley (2010). The Evolutionary Dynamics of Consciousness: An Integration of Eastern and Western Holistic Paradigms. Journal of Consciousness Studies 17 (9-10):9-10.score: 150.0
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  18. Carlos M. Parra & Masakazu Yano (2006). Evolutionary Dynamics of Knowledge. Complexity 11 (5):12-19.score: 150.0
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  19. Alexander Spradling (1993). Evolutionary Dynamics in Societal Development. World Futures 36 (2):203-210.score: 150.0
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  20. U. Wilensky & M. Novak (2010). Understanding Evolution as an Emergent Process: Learning with Agent-Based Models of Evolutionary Dynamics. In Roger S. Taylor & Michel Ferrari (eds.), Epistemology and Science Education: Understanding the Evolution Vs. Intelligent Design Controversy. Routledge.score: 150.0
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  21. Brian Skyrms (1992). Chaos and the Explanatory Significance of Equilibrium: Strange Attractors in Evolutionary Game Dynamics. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1992:374 - 394.score: 144.0
    This paper discusses the explanatory significance of the equilibrium concept in the context of an example of extremely complicated dynamical behavior. In particular, numerical evidence is presented for the existence of chaotic dynamics on a "strange attractor" in the evolutionary game dynamics introduced by Taylor and Jonker [also known as the "replicator dynamics"]. This phenomenon is present already in four strategy evolutionary games where the dynamics takes place in a simplex in three dimensional (...)
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  22. Joseph A. Marsh & Sarah A. Teichmann (2014). Parallel Dynamics and Evolution: Protein Conformational Fluctuations and Assembly Reflect Evolutionary Changes in Sequence and Structure. Bioessays 36 (2):209-218.score: 132.0
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  23. Seth Bullock & Mark A. Bedau, Exploring the Dynamics of Adaptation with Evolutionary Activity Plots.score: 126.0
    Evolutionary activity statistics and their visualization are introduced, and their motivation is explained. Examples of their use are described, and their strengths and limitations are discussed. References to more extensive or general accounts of these techniques are provided.
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  24. Elisabeth A. Lloyd (2000). Groups on Groups: Some Dynamics and Possible Resolution of the Units of Selection Debates in Evolutionary Biology. [REVIEW] Biology and Philosophy 15 (3):389-401.score: 126.0
    David Hull's analysis of conceptual change in science, as presentedin his book, Science as a Process (1988), provides a useful framework for understanding one of the scientific controversies in which he actively and constructively intervened, the units of selectiondebates in evolutionary biology. What follows is a brief overview ofthose debates and some reflections on them.
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  25. Jeffrey Ihara (1999). Darwinian Dynamics: Evolutionary Transitions in Fitness and Individuality by Richard E. Michod. Complexity 5 (1):42-43.score: 120.0
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  26. Norman A. Johnson & Richard E. Michod (1999). Cooperation and Conflict at All LevelsDarwinian Dynamics: Evolutionary Transitions in Fitness and Individuality. BioScience 49 (10):833.score: 120.0
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  27. Arthur J. Boucot & Peter S. Dawson (1990). Muddy Evolutionary Waters Macroevolutionary Dynamics Niles Eldredge. BioScience 40 (2):144-145.score: 120.0
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  28. Gabriel Dover (2000). How Genomic and Developmental Dynamics Affect Evolutionary Processes. Bioessays 22 (12):1153-1159.score: 120.0
  29. Ezio M. Insinna (1998). 11/L Nonlinear Dynamics in the Photoreceptor of the Unicellular Alga Euglena Gmcilis: An Application to the Evolutionary Aspects of Consciousness. In Stuart R. Hameroff, Alfred W. Kaszniak & A. C. Scott (eds.), Toward a Science of Consciousness Ii. Mit Press. 2--407.score: 120.0
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  30. P. S. Timiras (2002). Darwinian Dynamics: Evolutionary Transitions in Fitness and Individuality. By Richard E. Michod. The European Legacy 7 (4):532-532.score: 120.0
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  31. Brian Skyrms (1992). Chaos in Game Dynamics. Journal of Logic, Language and Information 1 (2):111-130.score: 102.0
    Two examples demonstrate the possibility of extremely complicated non-convergent behavior in evolutionary game dynamics. For the Taylor-Jonker flow, the stable orbits for three strategies were investigated by Zeeman. Chaos does not occur with three strategies. This papers presents numerical evidence that chaotic dynamics on a strange attractor does occur with four strategies. Thus phenomenon is closely related to known examples of complicated behavior in Lotka-Volterra ecological models.
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  32. Erika G. Schielke, Eric P. Palkovacs & David M. Post (2011). Eco-Evolutionary Feedbacks Drive Niche Differentiation in the Alewife. Biological Theory 6 (3):211-219.score: 90.0
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  33. Hannes Leitgeb (2005). Interpreted Dynamical Systems and Qualitative Laws: From Neural Networks to Evolutionary Systems. Synthese 146 (1-2):189 - 202.score: 84.0
    . Interpreted dynamical systems are dynamical systems with an additional interpretation mapping by which propositional formulas are assigned to system states. The dynamics of such systems may be described in terms of qualitative laws for which a satisfaction clause is defined. We show that the systems Cand CL of nonmonotonic logic are adequate with respect to the corresponding description of the classes of interpreted ordered and interpreted hierarchical systems, respectively. Inhibition networks, artificial neural networks, logic programs, and evolutionary (...)
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  34. Anya Plutynski (2006). Strategies of Model Building in Population Genetics. Philosophy of Science 73 (5):755-764.score: 84.0
    In 1966, Richard Levins argued that there are different strategies in model building in population biology. In this paper, I reply to Orzack and Sober’s (1993) critiques of Levins, and argue that his views on modeling strategies apply also in the context of evolutionary genetics. In particular, I argue that there are different ways in which models are used to ask and answer questions about the dynamics of evolutionary change, prospectively and retrospectively, in classical versus molecular (...) genetics. Further, I argue that robustness analysis is a tool for, if not confirmation, then something near enough, in this discipline. (shrink)
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  35. Donald S. Borrett, Saad Khan, Cynthia Lam, Danni Li, Hoa B. Nguyen & Hon C. Kwan (2006). Evolutionary Autonomous Agents and the Naturalization of Phenomenology. Phenomenology and the Cognitive Sciences 5 (3-4):351-363.score: 78.0
    The phenomenological goal of grounding the content of conceptual thought in the background understanding of everyday, skillful coping was approached using evolutionary autonomous agent (EAA) methodology. The behavior of an EAA evolved to perform a specified motor task was identified with skillful coping. Changes in the dynamics of the EAA controller occurred when the EAA encountered an unexpected obstacle with loss of longer time scale components in its hierarchical temporal organization. (...)
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  36. Roland Mühlenbernd (2011). Learning with Neighbours. Synthese 183 (S1):87-109.score: 72.0
    I present a game-theoretical multi-agent system to simulate the evolutionary process responsible for the pragmatic phenomenon division of pragmatic labour (DOPL), a linguistic convention emerging from evolutionary forces. Each agent is positioned on a toroid lattice and communicates via signaling games , where the choice of an interlocutor depends on the Manhattan distance between them. In this framework I compare two learning dynamics: reinforcement learning (RL) and belief learning (BL). An agent’s experiences from previous plays influence his (...)
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  37. Jeffrey Carpenter & Peter Hans Matthews (2005). No Switchbacks: Rethinking Aspiration-Based Dynamics in the Ultimatum Game. [REVIEW] Theory and Decision 58 (4):351-385.score: 72.0
    Aspiration-based evolutionary dynamics have recently been used to model the evolution of fair play in the ultimatum game showing that incredible threats to reject low offers persist in equilibrium. We focus on two extensions of this analysis: we experimentally test whether assumptions about agent motivations (aspiration levels) and the structure of the game (binary strategy space) reflect actual play, and we examine the problematic assumption embedded in the standard replicator dynamic that unhappy agents who switch strategies may return (...)
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  38. Stefan Artmann (2004). Four Principles of Evolutionary Pragmatics in Jacob's Philosophy of Modern Biology. Axiomathes 14 (4):381-395.score: 66.0
    The French molecular biologist François Jacob outlined a theory of evolution as tinkering. From a methodological point of view, his approach can be seen as a biologic specification of the relation between laws, describing coherently the dynamics of a system, and contingent boundary conditions on this dynamics. From a semiotic perspective, tinkering is a pragmatic concept well-known from the information-theoretic anthropology of Claude Lévi-Strauss. In idealized contrast to an engineer, the tinkerer has to accept the concrete restrictions on (...)
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  39. Fabrizio Germano (2007). Stochastic Evolution of Rules for Playing Finite Normal Form Games. Theory and Decision 62 (4):311-333.score: 66.0
    The evolution of boundedly rational rules for playing normal form games is studied within stationary environments of stochastically changing games. Rules are viewed as algorithms prescribing strategies for the different normal form games that arise. It is shown that many of the “folk results” of evolutionary game theory, typically obtained with a fixed game and fixed strategies, carry over to the present environments. The results are also related to some recent experiments on rules and games.
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  40. Roberta Dreon (2013). What is Evolutionary Aesthetics for? Aisthesis. Pratiche, Linguaggi E Saperi Dell’Estetico 6 (2):95-111.score: 66.0
    What is evolutionary aesthetics for? This paper investigates whether and in what way it may be useful to develop a conception of artistic practices as culturally differentiated behaviours in response to our vital needs, without resorting to a reductionist and substantial conception of human nature. Through an approach based on cultural naturalism, the suggested inquiry is also meant to verify whether in the debate on the evolutionary origins of the arts there are conceptual tools and theses which can (...)
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  41. Werner Güth, Friederike Mengel & Axel Ockenfels (2007). An Evolutionary Analysis of Buyer Insurance and Seller Reputation in Online Markets. Theory and Decision 63 (3):265-282.score: 66.0
    Applying an evolutionary framework, we investigate how a reputation mechanism and a buyer insurance (as used on Internet market platforms such as eBay) interact to promote trustworthiness and trust in markets with moral hazard problems. Our analysis suggests that the costs involved in giving reliable feedback determine the gains from trade that can be obtained in equilibrium. Buyer insurance, on the other hand, can affect the trading dynamics and equilibrium selection. We find that, under reasonable conditions, buyer insurance (...)
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  42. J. McKenzie Alexander (2003). Random Boolean Networks and Evolutionary Game Theory. Philosophy of Science 70 (5):1289-1304.score: 60.0
    Recent years have seen increased interest in the question of whether it is possible to provide an evolutionary game-theoretic explanation for certain kinds of social norms. I sketch a proof of a general representation theorem for a large class of evolutionary game-theoretic models played on a social network, in hope that this will contribute to a greater understanding of the long-term evolutionary dynamics of such models, and hence the evolution of social norms.
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  43. Till Grüne-Yanoff (2011). Evolutionary Game Theory, Interpersonal Comparisons and Natural Selection: A Dilemma. Biology and Philosophy 26 (5):637-654.score: 60.0
    When social scientists began employing evolutionary game theory (EGT) in their disciplines, the question arose what the appropriate interpretation of the formal EGT framework would be. Social scientists have given different answer, of which I distinguish three basic kinds. I then proceed to uncover the conceptual tension between the formal framework of EGT, its application in the social sciences, and these three interpretations. First, I argue that EGT under the biological interpretation has a limited application in the social sciences, (...)
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  44. Simon M. Huttegger (2007). Evolutionary Explanations of Indicatives and Imperatives. Erkenntnis 66 (3):409 - 436.score: 60.0
    Recently there has been some interest in studying the explanation of meaning by using signaling games. I shall argue that the meaning of signals in signaling games remains sufficiently unclear to motivate further investigation. In particular, the possibility of distinguishing imperatives and indicatives at a fundamental level will be explored. Thereby I am trying to preserve the generality of the signaling games framework while bringing it closer to human languages. A number of convergence results for the evolutionary dynamics (...)
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  45. Silvia Dell'orco & Mauro Maldonato (2011). Toward an Evolutionary Theory of Rationality. World Futures 66 (2):103-123.score: 60.0
    Since the dawn of time, humankind's singular ability to make decisions has allowed human beings to face innumerable environmental challenges and complex evolutionary dynamics. Environmental pressures are not so urgent anymore, comparing to our ancestors. Nonetheless, the number of decisions that contemporary humans are called to make is very high. During the last three centuries, the change from normative to descriptive theories, from formal to natural logic, from substantive to limited rationality has allowed us to explain how many (...)
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  46. Kevin N. Laland & Michael J. O'Brien (2011). Cultural Niche Construction: An Introduction. Biological Theory 6 (3):191-202.score: 60.0
  47. Klaus Jaffe (2001). On the Relative Importance of Haplo-Diploidy, Assortative Mating and Social Synergy on the Evolutionary Emergence of Social Behavior. Acta Biotheoretica 49 (1).score: 60.0
    Advances in multiagent simulation techniques make it possible to study more realistic dynamics of complex systems and allow evolutionary theories to be tested. Here I use simulations to assess the relative importance of reproductive systems (haplodiploidy vs. diploidy), mate selection (assortative mating vs. random mating) and social economics (pay-off matrices of evolutionary games) in the evolutionary dynamics leading to the emergence of social cooperation in the provision of parental care. The simulations confirm that haplo-diploid organisms (...)
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  48. Eduardo Viegas, Misako Takayasu, Wataru Miura, Koutarou Tamura, Takaaki Ohnishi, Hideki Takayasu & Henrik Jeldtoft Jensen (2013). Ecosystems Perspective on Financial Networks: Diagnostic Tools. Complexity 19 (1):22-36.score: 60.0
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  49. Randall D. Beer & Paul L. Williams (2014). Information Processing and Dynamics in Minimally Cognitive Agents. Cognitive Science 38 (7).score: 56.0
    There has been considerable debate in the literature about the relative merits of information processing versus dynamical approaches to understanding cognitive processes. In this article, we explore the relationship between these two styles of explanation using a model agent evolved to solve a relational categorization task. Specifically, we separately analyze the operation of this agent using the mathematical tools of information theory and dynamical systems theory. Information-theoretic analysis reveals how task-relevant information flows through the system to be combined into a (...)
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  50. J. McKenzie Alexander (2003). Random Boolean Networks and Evolutionary Game Theory. Philosophy of Science 70 (5):1289-1304.score: 54.0
    Recent years have seen increased interest in the question of whether it is possible to provide an evolutionary game theoretic explanation for certain kinds of social norms. These explanatory approaches often rely on the fact that, in certain evolutionary models, the basin of attraction of "fair" or "just" strategies occupies a certain percentage of the state space. I sketch a proof of a general representation theorem for a large class of evolutionary game theoretic models played on a (...)
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