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  1. Computation and Multiple Realizability.Marcin Miłkowski - 2016 - In Vincent C. Müller (ed.), Fundamental Issues of Artificial Intelligence. Cham: Springer. pp. 29-41.
    Multiple realizability (MR) is traditionally conceived of as the feature of computational systems, and has been used to argue for irreducibility of higher-level theories. I will show that there are several ways a computational system may be seen to display MR. These ways correspond to (at least) five ways one can conceive of the function of the physical computational system. However, they do not match common intuitions about MR. I show that MR is deeply interest-related, and for this reason, difficult (...)
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  • (1 other version)Giving up on convergence and autonomy: Why the theories of psychology and neuroscience are codependent as well as irreconcilable.Eric Hochstein - 2015 - Studies in History and Philosophy of Science Part A:1-19.
    There is a long-standing debate in the philosophy of mind and philosophy of science regarding how best to interpret the relationship between neuroscience and psychology. It has traditionally been argued that either the two domains will evolve and change over time until they converge on a single unified account of human behaviour, or else that they will continue to work in isolation given that they identify properties and states that exist autonomously from one another (due to the multiple-realizability of psychological (...)
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  • Integrating psychology and neuroscience: functional analyses as mechanism sketches.Gualtiero Piccinini & Carl Craver - 2011 - Synthese 183 (3):283-311.
    We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...)
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  • Neuroscience and the multiple realization of cognitive functions.Carrie Figdor - 2010 - Philosophy of Science 77 (3):419-456.
    Many empirically minded philosophers have used neuroscientific data to argue against the multiple realization of cognitive functions in existing biological organisms. I argue that neuroscientists themselves have proposed a biologically based concept of multiple realization as an alternative to interpreting empirical findings in terms of one‐to‐one structure‐function mappings. I introduce this concept and its associated research framework and also how some of the main neuroscience‐based arguments against multiple realization go wrong. *Received October 2009; revised December 2009. †To contact the author, (...)
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  • Multiple Realizability from a Causal Perspective.Lauren N. Ross - 2020 - Philosophy of Science 87 (4):640-662.
    This article examines the multiple realizability thesis within a causal framework. The beginnings of this framework are found in Elliott Sober’s “Multiple Realizability Argument against Reduction,”...
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  • Multiple Realizability and Biological Modality.Rami Koskinen - 2019 - Philosophy of Science 86 (5):1123-1133.
    Critics of multiple realizability have recently argued that we should concentrate solely on actual here-and-now realizations that are found in nature. The possibility of alternative, but unactualized, realizations is regarded as uninteresting because it is taken to be a question of pure logic or an unverifiable scenario of science fiction. However, in the biological context only a contingent set of realizations is actualized. Drawing on recent work on the theory of neutral biological spaces, the paper shows that we can have (...)
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  • The Functional Unity of Special Science Kinds.Daniel A. Weiskopf - 2011 - British Journal for the Philosophy of Science 62 (2):233-258.
    The view that special science properties are multiply realizable has been attacked in recent years by Shapiro, Bechtel and Mundale, Polger, and others. Focusing on psychological and neuroscientific properties, I argue that these attacks are unsuccessful. By drawing on interspecies physiological comparisons I show that diverse physical mechanisms can converge on common functional properties at multiple levels. This is illustrated with examples from the psychophysics and neuroscience of early vision. This convergence is compatible with the existence of general constraints on (...)
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  • How (Not) to Theorize About Multiple Realization.David Barrett - 2018 - Metaphilosophy 49 (5):674-690.
    Though multiple realization has been an important concept in the philosophy of mind and philosophy of psychology for more than fifty years, it has not been until quite recently that anyone proposed an actual theory of what multiple realization is. This paper argues that the most dominant current theories of multiple realization are unacceptable. It does so by mainly arguing for a particular methodology for theorizing about multiple realization. Rather than being mostly constrained by intuitions, as theorizing about folk notions (...)
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  • Multiple Realizability as a design heuristic in biological engineering.Rami Koskinen - 2018 - European Journal for Philosophy of Science 9 (1):15.
    Recently, several critics of the multiple realizability thesis have argued that philosophers have tended to accept the thesis on too weak grounds. On the one hand, the analytic challenge has problematized how philosophers have treated the multiple realization relation itself, claiming that assessment of the sameness of function and the relevant difference of realizers has been uncritical. On the other hand, it is argued that the purported evidence of the thesis is often left empirically unverified. This paper provides a novel (...)
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  • Computational explanation in neuroscience.Gualtiero Piccinini - 2006 - Synthese 153 (3):343-353.
    According to some philosophers, computational explanation is proprietary
    to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational explanation and outline some promising answers that (...)
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  • The Mind as Neural Software? Understanding Functionalism, Computationalism, and Computational Functionalism.Gualtiero Piccinini - 2010 - Philosophy and Phenomenological Research 81 (2):269-311.
    Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...)
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  • Neuroscience and multiple realization: a reply to Bechtel and Mundale.Ken Aizawa - 2009 - Synthese 167 (3):493-510.
    One trend in recent work on topic of the multiple realization of psychological properties has been an emphasis on greater sensitivity to actual science and greater clarity regarding the metaphysics of realization and multiple realization. One contribution to this trend is Bechtel and Mundale’s examination of the implications of brain mapping for multiple realization. Where Bechtel and Mundale argue that studies of brain mapping undermine claims about the multiple realization, this paper challenges that argument.
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  • One mechanism, many models: a distributed theory of mechanistic explanation.Eric Hochstein - 2016 - Synthese 193 (5):1387-1407.
    There have been recent disagreements in the philosophy of neuroscience regarding which sorts of scientific models provide mechanistic explanations, and which do not. These disagreements often hinge on two commonly adopted, but conflicting, ways of understanding mechanistic explanations: what I call the “representation-as” account, and the “representation-of” account. In this paper, I argue that neither account does justice to neuroscientific practice. In their place, I offer a new alternative that can defuse some of these disagreements. I argue that individual models (...)
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  • The strength of weak artificial consciousness.Anil Seth - 2009 - International Journal of Machine Consciousness 1 (1):71-82.
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