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Luca Rivelli
Université Catholique de Louvain
  1.  29
    Multilevel Ensemble Explanations: A Case From Theoretical Biology.Luca Rivelli - 2019 - Perspectives on Science 27 (1):88-116.
    In this paper I will reconstruct and analyze a famous argument by Stuart Kauffman about complex systems and evolution, in order to highlight the use in theoretical biology of a kind of non-mechanistic and non-causal explanation which I propose to call, following Kauffman, ensemble explanation. The aim is to contribute to the ongoing philosophical debate about non-causal explanations in the special sciences, kinds of explanation apparently extraneous to the received causal-mechanistic view. Ensemble explanations resemble quite closely the explanations of the (...)
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  2.  31
    Digital Literature Analysis for Empirical Philosophy of Science.Oliver M. Lean, Luca Rivelli & Charles H. Pence - 2021 - British Journal for the Philosophy of Science.
    Empirical philosophers of science aim to base their philosophical theories on observations of scientific practice. But since there is far too much science to observe it all, how can we form and test hypotheses about science that are sufficiently rigorous and broad in scope, while avoiding the pitfalls of bias and subjectivity in our methods? Part of the answer, we claim, lies in the computational tools of the digital humanities, which allow us to analyze large volumes of scientific literature. Here (...)
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    What Can Philosophers Really Learn From Science Journals?Oliver M. Lean, Luca Rivelli & Charles H. Pence - manuscript
    Philosophers of science regularly use scientific publications in their research. To make their analyses of the literature more thorough, some have begun to use computational methods from the digital humanities. Yet this creates a tension: it’s become a truism in science studies that the contents of scientific publications do not accurately reflect the complex realities of scientific investigation. In this paper, we outline existing views on how scientific publications fit into the broader picture of science as a system of practices, (...)
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  4. Antimodularity: Pragmatic Consequences of Computational Complexity on Scientific Explanation.Luca Rivelli - 2019 - In Matteo Vincenzo D'Alfonso & Don Berkich (eds.), On the Cognitive, Ethical, and Scientific Dimensions of Artificial Intelligence. Springer Verlag. pp. 97-122.
    This work is concerned with hierarchical modular descriptions, their algorithmic production, and their importance for certain types of scientific explanations of the structure and dynamical behavior of complex systems. Networks are taken into consideration as paradigmatic representations of complex systems. It turns out that algorithmic detection of hierarchical modularity in networks is a task plagued in certain cases by theoretical intractability and in most cases by the still high computational complexity of most approximated methods. A new notion, antimodularity, is then (...)
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