4 found
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  1. How to be a realist about computational neuroscience.Danielle J. Williams - 2025 - Synthese 205 (3):1-27.
    Recently, a version of realism has been offered to address the simplification strategies used in computational neuroscience. According to this view, computational models provide us with knowledge about the brain, but they should not be taken literally in _any_ sense, even rejecting the idea that the brain performs computations (computationalism). I acknowledge the need for considerations regarding simplification strategies in neuroscience and how they contribute to our interpretations of computational models; however, I argue that whether we should accept or reject (...)
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  2. Implementation and Interpretation: A Unified Account of Physical Computation.Danielle J. Williams - 2023 - Dissertation, University of California, Davis
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  3. Markov blankets: Realism and our ontological commitments.Danielle J. Williams - 2022 - Behavioral and Brain Sciences 45:e217.
    The authors argue that their target is orthogonal to the realism and instrumentalist debate. I argue that it is born directly from it. While the distinction is helpful in illuminating how some ontological commitments demand a theory of implementation, it's less clear whether different views cleanly map onto the epistemic and metaphysical uses defined in the paper.
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  4. It takes two to make a view go right. [REVIEW]Danielle J. Williams - 2024 - The Brains Blog.
    The Physical Signature of Computation is the most “robust” mapping view that’s ever hit the market. It is impressive in its detail and the careful attention paid to its characterization of both the physical system and the formal computational description—a true service to the philosophical literature. The book promises a “unified account of artifact and biological computation,” but here’s where things take a turn: after handling artifacts, the Robust Mapping Account fades from view and the Mechanistic Account of Physical Computation (...)
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