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Summary

The philosophy of cognitive science concerns philosophical issues that arise in cognitive science. Indeed, cognitive science is itself partly a philosophical project: it combines tools and insights from psychology, neuroscience, artificial intelligence, biology, anthropology, and philosophy. Initially unified by a commitment to a computational and representational outlook on cognition, cognitive science has increasingly come to embrace a wide variety of theoretical and methodological outlooks. Major questions that are being considered in the philosophy of cognitive science include: (i) Which (if any) cognitive processes or states are innate (in which organisms)? (ii) Should cognitive processes be seen as computational processes—and, if so, over what do they compute? (iii) What are the relationships between cognitive processes and neural (and other physiological) processes?

Key works Fodor 1983 is a classic—and still very influential—defense of the view that the mind consists of a handful of specialized and informationally encapsulated input and output systems, plus a central reasoning system. A more recent defense of a different, more empiricist view of cognition is in Prinz 2002 .
Introductions Two good introductions are: Clark 2001 Thagard 2007
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  1. Kenneth Aizawa (2001). Manfred Spitzer, the Mind Within the Net. Models of Learning, Thinking, and Acting. Minds and Machines 11 (3):445-448.
  2. Mark Alicke & David Rose (2010). Culpable Control or Moral Concepts? Behavioral and Brain Sciences 33 (04):330-331.
    Knobe argues in his target article that asymmetries in intentionality judgments can be explained by the view that concepts such as intentionality are suffused with moral considerations. We believe that the “culpable control” model of blame can account both for Knobe's side effect findings and for findings that do not involve side effects.
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  3. Anita L. Allen & Nicolle K. Strand (2015). Cognitive Enhancement and Beyond: Recommendations From the Bioethics Commission. Trends in Cognitive Sciences 19 (10):549-551.
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  4. C. Allen (1998). Review of Peter Carruthers' Language, Thought, and Consciousness. [REVIEW] Philosophical Psychology 11:91-94.
  5. Thomas R. Alley & Robert E. Shaw (1981). Principles of Learning and the Ecological Style of Inquiry. Behavioral and Brain Sciences 4 (1):139.
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  6. Jüri Allik & Anu Realo (2013). How is Freedom Distributed Across the Earth? Behavioral and Brain Sciences 36 (5):482-483.
    Although Van de Vliert presented an entertaining story containing several original observations, an implicit assumption that climate affects human society identically through the history is not realistic. If almost everything is explained by cold winters or hot summers, then nothing is explained. Ignoring rival explanations does not make the proposed theory more convincing.
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  7. H. F. Alrøe & E. Noe (2014). Authors’ Response: A Perspectivist View on the Perspectivist View of Interdisciplinary Science. Constructivist Foundations 10 (1):88-95.
    Upshot: In our response we focus on five questions that point to important common themes in the commentaries: why start in wicked problems, what kind of system is a scientific perspective, what is the nature of second-order research processes, what does this mean for understanding interdisciplinary work, and how may polyocular research help make real-world decisions.
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  8. H. F. Alrøe & E. Noe (2014). Communication, Autopoiesis and Semiosis. Constructivist Foundations 9 (2):183-185.
    Open peer commentary on the article “Social Autopoiesis?” by Hugo Urrestarazu. Upshot: We agree on the need to explore a concept of social autopoiesis that goes beyond a strictly human-centered concept of social systems as autopoietic communicative systems. But both Hugo Urrestarazu and Niklas Luhmann neglect the importance of semiosis in understanding communication, and this has important implications for the question of a more general approach to social systems.
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  9. H. F. Alrøe & E. Noe (2014). Second-Order Science of Interdisciplinary Research: A Polyocular Framework for Wicked Problems. Constructivist Foundations 10 (1):65-76.
    Context: The problems that are most in need of interdisciplinary collaboration are “wicked problems,” such as food crises, climate change mitigation, and sustainable development, with many relevant aspects, disagreement on what the problem is, and contradicting solutions. Such complex problems both require and challenge interdisciplinarity. Problem: The conventional methods of interdisciplinary research fall short in the case of wicked problems because they remain first-order science. Our aim is to present workable methods and research designs for doing second-order science in domains (...)
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  10. William P. Alston (1983). Dretske on Knowledge. Behavioral and Brain Sciences 6 (1):63.
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  11. Stuart A. Altmann (1984). Skinner's Circus. Behavioral and Brain Sciences 7 (4):678.
  12. Michael Alvard (2004). Good Hunters Keep Smaller Shares of Larger Pies. Behavioral and Brain Sciences 27 (4):560-561.
    High producers are motivated to hunt in spite of high levels of sharing because the transfers come from absolutely larger amounts of resource. In the context of a generalized cooperative subsistence strategy, stinginess could provoke the withdrawal of cooperative partners and result in a loss of income. Good producers could have more to lose by not sharing than poor producers would.
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  13. Julio Cabrera Álvarez (1984). Cortando árboles y relaciones (Una reflexión escéptica en torno a un tema de searle). Critica 16 (46):15 - 30.
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  14. Thomas J. Anastasio (2003). Probability Rather Than Logic as the Basis of Perception. Behavioral and Brain Sciences 26 (3):283-284.
    Formal logic may be an inappropriate framework for understanding perception. The responses of neurons at various levels of the sensory hierarchy may be better described in terms of probability than logic. Analysis and modeling of the multisensory responses of neurons in the midbrain provide a case study.
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  15. George J. Andersen (1994). Analysis of Information for 3-D Motion Perception: The Role of Eye Movements. Behavioral and Brain Sciences 17 (2):311.
  16. H. Andersen, P. Barker & X. Chen (1998). Kuhn's Theory of Scientific Revolutions and Cognitive Psychology. Philosophical Psychology 11 (1):5-28.
    In a previous article we have shown that Kuhn's theory of concepts is independently supported by recent research in cognitive psychology. In this paper we propose a cognitive re?reading of Kuhn's cyclical model of scientific revolutions: all of the important features of the model may now be seen as consequences of a more fundamental account of the nature of concepts and their dynamics. We begin by examining incommensurability, the central theme of Kuhn's theory of scientific revolutions, according to two different (...)
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  17. Hanne Andersen, Peter Barker & Xiang Chen (1996). Kuhn's Mature Philosophy of Science and Cognitive Psychology. Philosophical Psychology 9 (3):347 – 363.
    Drawing on the results of modem psychology and cognitive science we suggest that the traditional theory of concepts is no longer tenable, and that the alternative account proposed by Kuhn may now be seen to have independent empirical support quite apart from its success as part of an account of scientific change. We suggest that these mechanisms can also be understood as special cases of general cognitive structures revealed by cognitive science. Against this background, incommensurability is not an insurmountable obstacle (...)
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  18. Barton L. Anderson (2011). The Myth of Computational Level Theory and the Vacuity of Rational Analysis. Behavioral and Brain Sciences 34 (4):189-190.
    I extend Jones & Love's (J&L's) critique of Bayesian models and evaluate the conceptual foundations on which they are built. I argue that: (1) the part of Bayesian models is scientifically trivial; (2) theory is a fiction that arises from an inappropriate programming metaphor; and (3) the real scientific problems lie outside Bayesian theorizing.
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  19. John R. Anderson (1987). Methodologies for Studying Human Knowledge. Behavioral and Brain Sciences 10 (3):467.
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  20. John R. Anderson (1986). Category Learning: Things Aren't so Black and White. Behavioral and Brain Sciences 9 (4):651.
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  21. John R. Anderson, Jon M. Fincham, Yulin Qin & Andrea Stocco (2008). A Central Circuit of the Mind. Trends in Cognitive Sciences 12 (4):136-143.
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  22. John R. Anderson & Lynne M. Reder (1999). The Fan Effect: New Results and New Theories. Journal of Experimental Psychology: General 128 (2):186.
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  23. Michael C. Anderson & Benjamin Levy (2002). Repression Can Be Studied Empirically. Trends in Cognitive Sciences 6 (12):502-503.
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  24. Mike Anderson (1999). The Science of Life as Seen Through Rose-Coloured Glasses. Behavioral and Brain Sciences 22 (5):886-887.
    This commentary takes issue with two of Rose's central themes from the perspective of the psychology of intelligence. In the case of reductionism, I argue that Rose fails to live up to his own rhetoric by claiming a veto from his own discipline (biology) over facts of the matter in another (psychology). In the case of “Lifelines,” Rose's argument is contradicted by evidence from both individual differences and developmental change in intelligence.
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  25. R. Lanier Anderson (2002). Sensualism and Unconscious Representations in Nietzsche's Account of Knowledge. International Studies in Philosophy 34 (3):95-117.
  26. Rita E. Anderson (1987). Intelligence and Human Language. Behavioral and Brain Sciences 10 (4):657.
  27. Robert M. Anderson & Joseph F. Gonsalves (1981). Sensory Suppression and the Unity of Consciousness. Behavioral and Brain Sciences 4 (1):99.
  28. József Andor (1980). Some Remarks on the Notion of Competence. Behavioral and Brain Sciences 3 (1):15.
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  29. James Andow (2016). Qualitative Tools & Experimental Philosophy. Philosophical Psychology.
    Experimental philosophy brings empirical methods to philosophy. These methods are used to probe how people think about philosophically interesting things such as knowledge, morality, freedom, etc. This paper explores the contribution that qualitative methods have to make in this enterprise. I argue that qualitative methods have the potential to make a much greater contribution than they have so far. Along the way, I acknowledge a few types of resistance that proponents of qualitative methods in experimental philosophy might encounter, and provide (...)
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  30. James Andow (2016). Reliable but Not Home Free? What Framing Effects Mean for Moral Intuitions. Philosophical Psychology 29 (6):904-911.
    Various studies show moral intuitions to be susceptible to framing effects. Many have argued that this susceptibility is a sign of unreliability and that this poses a methodological challenge for moral philosophy. Recently, doubt has been cast on this idea. It has been argued that extant evidence of framing effects does not show that moral intuitions have an unreliability problem. I argue that, even if the extant evidence suggests that moral intuitions are fairly stable with respect to what intuitions we (...)
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  31. John H. Andreae (1978). On Inference From Input/Output. Behavioral and Brain Sciences 1 (2):226.
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  32. John H. Andreae & Shaun W. Ryan (1994). Associative Learning and Task Complexity. Behavioral and Brain Sciences 17 (2):357.
  33. N. C. Andreasen (2011). A Journey Into Chaos: Creativity and the Unconscious. Mens Sana Monographs 9 (1):42.
    The capacity to be creative, to produce new concepts, ideas, inventions, objects or art, is perhaps the most important attribute of the human brain. We know very little, however, about the nature of creativity or its neural basis. Some important questions include how should we define creativity? How is it related (or unrelated) to high intelligence? What psychological processes or environmental circumstance cause creative insights to occur? How is it related to conscious and unconscious processes? What is happening at the (...)
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  34. Nancy C. Andreasen (1982). There May Be a “Schizophrenic Language”. Behavioral and Brain Sciences 5 (4):588.
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  35. Chrisoula Andreou (2008). Addiction, Procrastination, and Failure Points in Decision-Making Systems. Behavioral and Brain Sciences 31 (4):439-440.
    Redish et al. suggest that their failures-in-decision-making framework for understanding addiction can also contribute to improving our understanding of a variety of psychiatric disorders. In the spirit of reflecting on the significance and scope of their research, I briefly develop the idea that their framework can also contribute to improving our understanding of the pervasive problem of procrastination.
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  36. Lori L. Holt Andrew J. Lotto, Gregory S. Hickok (2009). Reflections on Mirror Neurons and Speech Perception. Trends in Cognitive Sciences 13 (3):110.
  37. Larry L. Jacoby Andrew P. Yonelinas (2012). The Process-Dissociation Approach Two Decades Later: Convergence, Boundary Conditions, and New Directions. Memory and Cognition 40 (5):663-680.
    The process-dissociation procedure was developed to separate the controlled and automatic contributions of memory. It has spawned the development of a host of new measurement approaches and has been applied across a broad range of fields in the behavioral sciences, ranging from studies of memory and perception to neuroscience and social psychology. Although it has not been without its shortcomings or critics, its growing influence attests to its utility. In the present article, we briefly review the factors motivating its development, (...)
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  38. R. J. Andrew (1988). Contiguity, Contingency, and Causation. Behavioral and Brain Sciences 11 (3):447.
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  39. David B. Andrews (1991). Extending Neuropsychology. Behavioral and Brain Sciences 14 (3):439-440.
  40. P. L. R. Andrews & I. N. C. Lawes (1990). Classification of Afferents by Input Not by Output? Behavioral and Brain Sciences 13 (2):300-301.
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  41. Paul W. Andrews, Steven W. Gangestad & Dan Matthews (2002). Adaptationism, Exaptationism, and Evolutionary Behavioral Science. Behavioral and Brain Sciences 25 (4):534-547.
    In our target article, we discussed the standards of evidence that could be used to identify adaptations, and argued that building an empirical case that certain features of a trait are best explained by exaptation, spandrel, or constraint requires the consideration, testing, and rejection of adaptationist hypotheses. We are grateful to the 31 commentators for their thoughtful insights. They raised important issues, including the meaning of “exaptation”; whether Gould and Lewontin's critique of adaptationism was primarily epistemological or ontological; the necessity, (...)
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  42. Paul W. Andrews, Steven W. Gangestad & Dan Matthews (2002). Adaptationism – How to Carry Out an Exaptationist Program. Behavioral and Brain Sciences 25 (4):489-504.
    1 Adaptationism is a research strategy that seeks to identify adaptations and the specific selective forces that drove their evolution in past environments. Since the mid-1970s, paleontologist Stephen J. Gould and geneticist Richard Lewontin have been critical of adaptationism, especially as applied toward understanding human behavior and cognition. Perhaps the most prominent criticism they made was that adaptationist explanations were analogous to Rudyard Kipling's Just So Stories. Since storytelling is an inherent part of science, the criticism refers to the acceptance (...)
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  43. James Rowland Angell (1906). Recent Discussion of Feeling. Journal of Philosophy, Psychology and Scientific Methods 3 (7):169-174.
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  44. James Rowland Angell (1903). The Relations of Structural and Functional Psychology to Philosophy. Philosophical Review 12 (3):243-271.
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  45. Hymie Anisman (1982). Anhedonia: Too Much, Too Soon. Behavioral and Brain Sciences 5 (1):53.
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  46. Hymie Anisman (1980). Depression and Suicide: Stress as a Precipitating Factor. Behavioral and Brain Sciences 3 (2):272.
  47. Hymie Anisman & Robert M. Zacharko (1982). Assessing Internal Affairs. Behavioral and Brain Sciences 5 (3):422.
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  48. Jaap Jacobson Anne (2006). Tenure and the Political Autonomy of Faculty Inquiry. Behavioral and Brain Sciences 29 (6).
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  49. Marian Annett (1991). Predicting From the Right Shift Theory. Behavioral and Brain Sciences 14 (2):338-341.
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  50. Marian Annett (1980). Sex Differences in Laterality– Meaningfulness Versus Reliability. Behavioral and Brain Sciences 3 (2):227.
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