Search results for 'A. Dietrich' (try it on Scholar)

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Profile: Ayse Dietrich (Middle East Technical University)
  1. Donald J. Dietrich (2012). Dietrich Bonhoeffer's Letters and Papers From Prison: A Biography. By Martin Marty. The European Legacy 17 (7):951-952.score: 1260.0
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  2. Roberta L. Millstein, Robert A. Skipper Jr & Michael R. Dietrich (2009). (Mis)Interpreting Mathematical Models: Drift as a Physical Process. Philosophy and Theory in Biology 1 (20130604):e002.score: 660.0
    Recently, a number of philosophers of biology (e.g., Matthen and Ariew 2002; Walsh, Lewens, and Ariew 2002; Pigliucci and Kaplan 2006; Walsh 2007) have endorsed views about random drift that, we will argue, rest on an implicit assumption that the meaning of concepts such as drift can be understood through an examination of the mathematical models in which drift appears. They also seem to implicitly assume that ontological questions about the causality (or lack thereof) of terms appearing in the models (...)
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  3. By Fred Adams & Laura A. Dietrich (2004). What's in a (N Empty) Name? Pacific Philosophical Quarterly 85 (2):125–148.score: 540.0
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  4. Michael R. Dietrich & Robert A. Skipper Jr (2012). A Shifting Terrain: A Brief History of the Adaptive Landscape. In E. Svensson & R. Calsbeek (eds.), The Adaptive Landscape in Evolutionary Biology. Oup Oxford.score: 540.0
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  5. Fred Adams & Laura A. Dietrich (2004). What's in a (N Empty) Name? Pacific Philosophical Quarterly 85 (2):125-148.score: 540.0
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  6. Eric Dietrich (2001). Concepts: Fodor's Little Semantic BBs of Thought - A Critical Look at Fodor's Theory of Concepts -. J. Of Experimental and Theoretical AI 13 (2):89-94.score: 420.0
    I find it interesting that AI researchers don't use concepts very often in their theorizing. No doubt they feel no pressure to. This is because most AI researchers do use representations which allow a system to chunk up its environment, and basically all we know about concepts is that they are representations which allow a system to chunk up its environment.
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  7. Eric Dietrich (1999). Dynamic Systems and Paradise Regained, or How to Avoid Being a Calculator. [REVIEW] J. Of Experimental and Theoretical AI 11 (4):473-478.score: 420.0
    The new kid on the block in cognitive science these days is dynamic systems. This way of thinking about the mind is, as usual, radically opposed to computationalism - - the hypothesis that thinking is computing. The use of dynamic systems is just the latest in a series of attempts, from Searle's Chinese Room Argument, through the weirdnesses of postmodernism, to overthrown computationalism, which as we all know is a perfectly nice hypothesis about the mind that never hurt anyone.
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  8. Eric Dietrich (2008). The Bishop and Priest: Toward a Point-of-View Based Epistemology of True Contradictions. Logos Architekton 2 (2):35-58..score: 420.0
    True contradictions are taken increasingly seriously by philosophers and logicians. Yet, the belief that contradictions are always false remains deeply intuitive. This paper confronts this belief head-on by explaining in detail how one specific contradiction is true. The contradiction in question derives from Priest's reworking of Berkeley's argument for idealism. However, technical aspects of the explanation offered here differ considerably from Priest's derivation. The explanation uses novel formal and epistemological tools to guide the reader through a valid argument with, not (...)
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  9. Franz Dietrich & Christian List (2013). A Reason-Based Theory of Rational Choice. Noûs 47 (1):104-134.score: 420.0
    There is a surprising disconnect between formal rational choice theory and philosophical work on reasons. The one is silent on the role of reasons in rational choices, the other rarely engages with the formal models of decision problems used by social scientists. To bridge this gap, we propose a new, reason-based theory of rational choice. At its core is an account of preference formation, according to which an agent’s preferences are determined by his or her motivating reasons, together with a (...)
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  10. Eric Dietrich (2001). AI, Concepts, and the Paradox of Mental Representation, with a Brief Discussion of Psychological Essentialism. J. Of Exper. And Theor. AI 13 (1):1-7.score: 420.0
    Mostly philosophers cause trouble. I know because on alternate Thursdays I am one -- and I live in a philosophy department where I watch all of them cause trouble. Everyone in artificial intelligence knows how much trouble philosophers can cause (and in particular, we know how much trouble one philosopher -- John Searle -- has caused). And, we know where they tend to cause it: in knowledge representation and the semantics of data structures. This essay is about a recent case (...)
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  11. Eric Dietrich (2000). A Counterexample T o All Future Dynamic Systems Theories of Cognition. J. Of Experimental and Theoretical AI 12 (2):377-382.score: 420.0
    Years ago, when I was an undergraduate math major at the University of Wyoming, I came across an interesting book in our library. It was a book of counterexamples t o propositions in real analysis (the mathematics of the real numbers). Mathematicians work more or less like the rest of us. They consider propositions. If one seems to them to be plausibly true, then they set about to prove it, to establish the proposition as a theorem. Instead o f setting (...)
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  12. Eric Dietrich (2001). Banbury Bound, or Can a Machine Be Conscious? J. Of Experimental and Theoretical AI 13 (2):177-180.score: 420.0
    In mid-May of 2001, I attended a fascinating workshop at Cold Spring Harbor Labs. The conference was held at the lab's Banbury Center, an elegant mansion and its beautiful surrounding estate, located on Banbury Lane, in the outskirts of Lloyd Harbor, overlooking the north shore of Long Island in New York. The estate was formerly owned by Charles Sammis Robertson. In 1976, Robertson donated his estate, and an endowment for its upkeep, to the Lab. The donation included the Robertson's mansion, (...)
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  13. Franz Dietrich & Christian List (2010). The Aggregation of Propositional Attitudes: Towards a General Theory. Oxford Studies in Epistemology 3.score: 420.0
    How can the propositional attitudes of several individuals be aggregated into overall collective propositional attitudes? Although there are large bodies of work on the aggregation of various special kinds of propositional attitudes, such as preferences, judgments, probabilities and utilities, the aggregation of propositional attitudes is seldom studied in full generality. In this paper, we seek to contribute to filling this gap in the literature. We sketch the ingredients of a general theory of propositional attitude aggregation and prove two new theorems. (...)
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  14. Frank Dietrich (2013). Secession of the Rich: A Qualified Defense. Politics, Philosophy and Economics 13 (1):1470594-13483480.score: 420.0
    The secession of prosperous regions may negatively affect the redistributive scheme of an established state. As a consequence, the capacity of its welfare system to support the inhabitants of poorer regions may be significantly reduced. Some authors assert that affluent groups who opt for full political independence violate duties of solidarity. This objection to the secession of prosperous regions can be based on different views of distributive justice. Here, following a distinction that has been introduced by Allen Buchanan, ‘subject centred’ (...)
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  15. Christian List & Franz Dietrich, Mentalism Versus Behaviourism in Economics: A Philosophy-of-Science Perspective.score: 420.0
    Behaviourism is the view that preferences, beliefs, and other mental states in social-scientific theories are nothing but constructs re-describing people's behavioural dispositions. Mentalism is the view that they capture real phenomena, no less existent than the unobservable entities and properties in the natural sciences, such as electrons and electromagnetic fields. While behaviourism has long gone out of fashion in psychology and linguistics, it remains influential in economics, especially in `revealed preference' theory. We aim to (i) clear up some common confusions (...)
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  16. Franz Dietrich, A Liberal Paradox for Judgment Aggregation.score: 420.0
    In the emerging literature on judgment aggregation over logically connected propositions, expert rights or liberal rights have not been investigated yet. A group making collective judgments may assign individual members or subgroups with expert knowledge on, or particularly a¤ected by, certain propositions the right to determine the collective judgment on those propositions. We identify a problem that generalizes Sen’s ‘liberal paradox’. Under plausible conditions, the assignment of rights to two or more individuals or subgroups is inconsistent with the unanimity principle, (...)
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  17. Franz Dietrich & Christian List (2011). A Model of Non-Informational Preference Change. Journal of Theoretical Politics 23 (2):145-164.score: 420.0
    According to standard rational choice theory, as commonly used in political science and economics, an agent's fundamental preferences are exogenously fixed, and any preference change over decision options is due to Bayesian information learning. Although elegant and parsimonious, such a model fails to account for preference change driven by experiences or psychological changes distinct from information learning. We develop a model of non-informational preference change. Alternatives are modelled as points in some multidimensional space, only some of whose dimensions play a (...)
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  18. Franz Dietrich, A Generalised Model of Judgment Aggregation.score: 420.0
    The new …eld of judgment aggregation aims to merge many individual sets of judgments on logically interconnected propositions into a single collective set of judgments on these propositions. Judgment aggregation has commonly been studied using classical propositional logic, with a limited expressive power and a problematic representation of conditional statements (“if P then Q”) as material conditionals. In this methodological paper, I present a simple uni…ed model of judgment aggregation in general logics. I show how many realistic decision problems can (...)
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  19. Franz Dietrich & Christian List (2004). A Model of Jury Decisions Where All Jurors Have the Same Evidence. Synthese 142 (2):175 - 202.score: 420.0
    Under the independence and competence assumptions of Condorcet’s classical jury model, the probability of a correct majority decision converges to certainty as the jury size increases, a seemingly unrealistic result. Using Bayesian networks, we argue that the model’s independence assumption requires that the state of the world (guilty or not guilty) is the latest common cause of all jurors’ votes. But often – arguably in all courtroom cases and in many expert panels – the latest such common cause is a (...)
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  20. Eric Dietrich, -EDITORIAL- Banbury Bound, or Can a Machine Be Conscious?score: 420.0
    In mid-May of 2001, I attended a fascinating workshop at Cold Spring Harbor Labs. The conference was held at the lab's Banbury Center, an elegant mansion and its beautiful surrounding estate, located on Banbury Lane, in the outskirts of Lloyd Harbor, overlooking the north shore of Long Island in New York. The estate was formerly owned by Charles Sammis Robertson. In 1976, Robertson donated his estate, and an endowment for its upkeep, to the Lab. The donation included the Robertson's mansion, (...)
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  21. John Dietrich & Caitlyn Witkowski (2012). Obama's Human Rights Policy: Déjà Vu with a Twist. Human Rights Review 13 (1):39-64.score: 420.0
    In US history, much human rights policy developed in four waves during the twentieth century. These waves were triggered by similar circumstances, but all proved short-lived as structural constraints such as limited US power over other countries’ domestic actions, competing US policy priorities, a US hesitance to join multilateral institutions, and the continued domestic political weakness of human rights advocates led to setbacks. As Barack Obama took office, his campaign comments and the past patterns led to widespread expectations that he (...)
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  22. Eric Dietrich & Valerie Gray Hardcastle (2002). A Connecticut Yalie in King Descartes' Court. Newsletter of Cognitive Science Society (Now Defunct).score: 360.0
    What is consciousness? Of course, each of us knows, privately, what consciousness is. And we each think, for basically irresistible reasons, that all other conscious humans by and large have experiences like ours. So we conclude that we all know what consciousness is. It's the felt experiences of our lives. But that is not the answer we, as cognitive scientists, seek in asking our question. We all want to know what physical process consciousness is and why it produces this very (...)
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  23. Eric Dietrich (1998). It Only Seems as If Zombies Are Logically Possible, or How Consciousness Hides the Truth of Materialism: A Critical Review of The Conscious Mind. [REVIEW] Minds and Machines 8 (3):441-461.score: 360.0
  24. Eric Dietrich & Valerie Gray Hardcastle, A Connecticut Yalie in King Descartes' Court.score: 360.0
    What is consciousness? Of course, each of us knows, privately, what consciousness is. And we each think, for basically irresistible reasons, that all other conscious humans by and large have experiences like ours. So we conclude that we all know what consciousness is. It's the felt experiences of our lives. But that is not the answer we, as cognitive scientists, seek in asking our question. We all want to know what physical process consciousness is and why it produces this very (...)
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  25. Eric Dietrich & Arthur B. Markman (1998). All Information Processing Entails Computation, or, If R. A. Fisher Had Been a Cognitive Scientist . . Behavioral and Brain Sciences 21 (5):637-638.score: 360.0
    We argue that the dynamical and computational hypotheses are compatible and in fact need each other: they are about different aspects of cognition. However, only computationalism is about the information-processing aspect. We then argue that any form of information processing relying on matching and comparing, as cognition does, must use discrete representations and computations defined over them.
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  26. Jessica S. Dietrich (2011). Silius (A.) Augoustakis (Ed.) Brill's Companion to Silius Italicus. Pp. Xxii + 512. Leiden and Boston: Brill, 2010. Cased, €152, US$225. ISBN: 978-90-04-16570-0. [REVIEW] The Classical Review 61 (02):480-483.score: 360.0
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  27. Donald J. Dietrich (2013). Old Believers in a Changing World. The European Legacy 18 (5):655-656.score: 360.0
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  28. Chris Fields & Eric Dietrich (1987). Intentionality is a Red Herring. Behavioral and Brain Sciences 10 (4):756.score: 360.0
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  29. John W. Dietrich (2011). A Foreigner Carrying in the Crook of His Arm a Tiny Bomb by Amitava Kumar. Human Rights Review 12 (4):549-551.score: 360.0
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  30. Joan M. Dietrich & R. B. Payne (1983). Psychomotor Reminiscence as a Function of Sex and Amount of Prerest Practice. Bulletin of the Psychonomic Society 21 (5):377-380.score: 360.0
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  31. Eric Dietrich (2003). An ABSURDIST Model Vindicates a Venerable Theory. Trends in Cognitive Sciences 7 (2):57-59.score: 360.0
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  32. Ayse Dietrich & Richard Dietrich (2007). A Proposed Identification for Zosima's Apolikaptii Monastery in Constantinople. Byzantion 77:116-123.score: 360.0
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  33. G. Dietrich (1985). Perspectives of a Feminist Theology-Total Humanity for Women and Men. ARGUMENT 27 (SEP):669-686.score: 360.0
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  34. D. J. Dietrich (2001). The Good Listener, Helen Bamber: A Life Against Cruelty. By Neil Belton. The European Legacy 6 (3):388-388.score: 360.0
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  35. Wendell S. Dietrich (1993). Troeltsch's Treatment of the Thomist Synthesis in the Social Teaching as a Signal of His View of a New Cultural Synthesis. The Thomist 57 (3):381-401.score: 360.0
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  36. Valerie Gray Hardcastle & Eric Dietrich (2001). Toward a Book of Counter-Examples for Cognitive Science: Dynamic Systems Theory, Emotion, and Aardvarks. Danish Yearbook of Philosophy 36:35-48.score: 360.0
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  37. E. O. James & B. C. Dietrich (1966). Death, Fate and the Gods: The Development of a Religious Idea in Greek Popular Belief and in Homer. Journal of Hellenic Studies 86:234.score: 360.0
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  38. Eric Dietrich (2001). It Does So. [REVIEW] AI Magazine 22 (4):141-144.score: 300.0
    Objections to AI and computational cognitive science are myriad. Accordingly, there are many different reasons for these attacks. But all of them come down to one simple observation: humans seem a lot smarter that computers -- not just smarter as in Einstein was smarter than I, or I am smarter than a chimpanzee, but more like I am smarter than a pencil sharpener. To many, computation seems like the wrong paradigm for studying the mind. (Actually, I think there are deeper (...)
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  39. Frederick R. Adams & Laura A. Dietrich (2004). Swampman's Revenge: Squabbles Among the Representationalists. Philosophical Psychology 17 (3):323-40.score: 300.0
    There are both externalist and internalist theories of the phenomenal content of conscious experiences. Externalists like Dretske and Tye treat the phenomenal content of conscious states as representations of external properties (and events). Internalists think that phenomenal conscious states are reducible to electrochemical states of the brain in the style of the type-type identity theory. In this paper, we side with the representationalists and visit a dispute between them over the test case of Swampman. Does Swampman have conscious phenomenal (...)
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  40. Eric Dietrich & Valerie Gray Hardcastle (2004). Sisyphus's Boulder: Consciousness and the Limits of the Knowable. John Benjamins.score: 300.0
    In Sisyphus's Boulder, Eric Dietrich and Valerie Hardcastle argue that we will never get such a theory because consciousness has an essential property that...
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  41. Eric Dietrich & A. Markman (2003). Discrete Thoughts: Why Cognition Must Use Discrete Representations. Mind and Language 18 (1):95-119.score: 300.0
    Advocates of dynamic systems have suggested that higher mental processes are based on continuous representations. In order to evaluate this claim, we first define the concept of representation, and rigorously distinguish between discrete representations and continuous representations. We also explore two important bases of representational content. Then, we present seven arguments that discrete representations are necessary for any system that must discriminate between two or more states. It follows that higher mental processes require discrete representations. We also argue that discrete (...)
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  42. L. A. Loren & Eric Dietrich (1997). Merleau-Ponty, Embodied Cognition, and the Problem of Intentionality. Cybernetics and Systems 28:345-58.score: 300.0
  43. Franz Dietrich & Christian List (2013). Reasons for (Prior) Belief in Bayesian Epistemology. Synthese 190 (5):781-786.score: 300.0
    Bayesian epistemology tells us with great precision how we should move from prior to posterior beliefs in light of new evidence or information, but says little about where our prior beliefs come from. It offers few resources to describe some prior beliefs as rational or well-justified, and others as irrational or unreasonable. A different strand of epistemology takes the central epistemological question to be not how to change one’s beliefs in light of new evidence, but what reasons justify a given (...)
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  44. Eric Dietrich (2001). It Does So: Review of Jerry Fodor, The Mind Doesn't Work That Way. [REVIEW] AI Magazine 22 (4):121-24.score: 300.0
    Objections to AI and computational cognitive science are myriad. Accordingly, there are many different reasons for these attacks. But all of them come down to one simple observation: humans seem a lot smarter that computers -- not just smarter as in Einstein was smarter than I, or I am smarter than a chimpanzee, but more like I am smarter than a pencil sharpener. To many, computation seems like the wrong paradigm for studying the mind. (Actually, I think there are deeper (...)
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  45. Eric Dietrich (2001). It Does So: Review of The Mind Doesn't Work That Way: The Scope and Limits of Computational Psychology. [REVIEW] AI Magazine 22 (4):141-144.score: 300.0
    Objections to AI and computational cognitive science are myriad. Accordingly, there are many different reasons for these attacks. But all of them come down to one simple observation: humans seem a lot smarter that computers -- not just smarter as in Einstein was smarter than I, or I am smarter than a chimpanzee, but more like I am smarter than a pencil sharpener. To many, computation seems like the wrong paradigm for studying the mind. (Actually, I think there are deeper (...)
     
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  46. Michael R. Dietrich & Robert A. Skipper (2007). Manipulating Underdetermination in Scientific Controversy: The Case of the Molecular Clock. Perspectives on Science 15 (3):295-326.score: 300.0
    : Where there are cases of underdetermination in scientific controversies, such as the case of the molecular clock, scientists may direct the course and terms of dispute by playing off the multidimensional framework of theory evaluation. This is because assessment strategies themselves are underdetermined. Within the framework of assessment, there are a variety of trade-offs between different strategies as well as shifting emphases as specific strategies are given more or less weight in assessment situations. When a strategy is underdetermined, scientists (...)
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  47. A. Dietrich (2003). Functional Neuroanatomy of Altered States of Consciousness: The Transient Hypofrontality Hypothesis. Consciousness and Cognition 12 (2):231-256.score: 240.0
  48. A. Dietrich (2004). Neurocognitive Mechanisms Underlying the Experience of Flow. Consciousness and Cognition 13 (4):746-761.score: 240.0
  49. Eric A. Weiss, Justin Leiber, Judith Felson Duchan, Mallory Selfridge, Eric Dietrich, Peter A. Facione, Timothy Joseph Day, Johan M. Lammens, Andrew Feenberg, Deborah G. Johnson, Daniel S. Levine & Ted A. Warfield (1995). Book Reviews. [REVIEW] Minds and Machines 5 (1):109-155.score: 240.0
  50. Kevin J. Peterson, Michael R. Dietrich & Mark A. McPeek (2009). MicroRNAs and Metazoan Macroevolution: Insights Into Canalization, Complexity, and the Cambrian Explosion. Bioessays 31 (7):736-747.score: 240.0
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