Relevant bibliographies by topics / Philosophy and explanation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Philosophy and explanation'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Philosophy and explanation"

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Clark, Stephen R. L. "The Limits of Explanation: Limited Explanations." Royal Institute of Philosophy Supplement 27 (March 1990): 195–210. http://dx.doi.org/10.1017/s1358246100005117.

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When I was first approached to read a paper at the conference from which this volume takes its beginning I expected that Flint Schier, with whom I had taught a course on the Philosophy of Biology in my years at Glasgow, would be with us to comment and to criticize. I cannot let this occasion pass without expressing once again my own sense of loss. I am sure that we would all have gained by his presence, and hope that he would find things both to approve, and disapprove, in the following venture.
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Schouten, Gina. "Philosophy in Schools: Can Early Exposure Help Solve Philosophy's Gender Problem?" Hypatia 31, no. 2 (2016): 275–92. http://dx.doi.org/10.1111/hypa.12232.

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In this article, I explore a new reason in favor of precollegiate philosophy: It could help narrow the persistent gender disparity within the discipline. I catalog some of the most widely endorsed explanations for the underrepresentation of women in philosophy and argue that, on each hypothesized explanation, precollegiate philosophy instruction could help improve our discipline's gender balance. Explanations I consider include stereotype threat, gendered philosophical intuitions, inhospitable disciplinary environment, lack of same‐sex role models for women students in philosophy, and conflicting “schemas” for philosophy and femininity. I argue that, insofar as some combination of these hypothesized explanations accounts for some portion of the underrepresentation of women in philosophy, those of us concerned to make things better have reason to participate in and promote efforts to share philosophy with younger students.
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McLaughlin, P. "Mechanical philosophy and artefact explanation." Studies in History and Philosophy of Science Part A 37, no. 1 (March 2006): 97–101. http://dx.doi.org/10.1016/j.shpsa.2005.12.010.

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Hardcastle, Valerie Gray. "[Explanation] Is Explanation Better." Philosophy of Science 64, no. 1 (March 1997): 154–60. http://dx.doi.org/10.1086/392540.

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O’Brien, Lilian. "Action explanation and its presuppositions." Canadian Journal of Philosophy 49, no. 1 (February 2019): 123–46. http://dx.doi.org/10.1080/00455091.2018.1518629.

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AbstractIn debates about rationalizing action explanation causalists assume that the psychological states that explain an intentional action have both causal and rational features. I scrutinize the presuppositions of those who seek and offer rationalizing action explanations. This scrutiny shows, I argue, that where rational features play an explanatory role in these contexts, causal features play only a presuppositional role. But causal features would have to play an explanatory role if rationalizing action explanation were a species of causal explanation. Consequently, it is not a species of causal explanation.
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Lehrer, Keith. "Ultimate Preference and Explanation." Grazer Philosophische Studien 97, no. 4 (November 24, 2020): 600–615. http://dx.doi.org/10.1163/18756735-00000125.

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Abstract The articles by Corlett, McKenna and Waller in the present issue call for some further enlightenment on Lehrer’s defense of classical compatibilism. Ultimate explanation in terms of a power preference, which is the primary explanation for choice, is now the central feature of his defense. This includes the premise that scientific determinism may fail to explain our choices. Sylvain Bromberger (1965) showed that nomological deduction is not sufficient for explanation. A power preference, which is by definition a preference over alternatives, is the primary explanation when the power preference explains the choice without the need to appeal to anything else, including even anything that explains it. The author notes that explanation is not generally transitive. The power preference must stand alone as an ultimate explanation independent of other explanations. It is thus the ultimate preference over alternatives of choice.
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Bradie, Michael. "Explanation." Teaching Philosophy 12, no. 3 (1989): 291–93. http://dx.doi.org/10.5840/teachphil198912377.

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Nelson, Alan. "Explanation and Justification in Political Philosophy." Ethics 97, no. 1 (October 1986): 154–76. http://dx.doi.org/10.1086/292824.

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Reutlinger, Alexander. "Explanation beyond causation? New directions in the philosophy of scientific explanation." Philosophy Compass 12, no. 2 (February 2017): e12395. http://dx.doi.org/10.1111/phc3.12395.

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Castro, Eduardo. "A deductive-nomological model for mathematical scientific explanation." Principia: an international journal of epistemology 24, no. 1 (April 28, 2020): 1–27. http://dx.doi.org/10.5007/1808-1711.2020v24n1p1.

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I propose a deductive-nomological model for mathematical scientific explanation. In this regard, I modify Hempel’s deductive-nomological model and test it against some of the following recent paradigmatic examples of the mathematical explanation of empirical facts: the seven bridges of Königsberg, the North American synchronized cicadas, and Hénon-Heiles Hamiltonian systems. I argue that mathematical scientific explanations that invoke laws of nature are qualitative explanations, and ordinary scientific explanations that employ mathematics are quantitative explanations. I analyse the repercussions of this deductivenomological model on causal explanations.
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Dissertations / Theses on the topic "Philosophy and explanation"

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Quinn, Laleh Kathleen. "Consciousness and explanation." Diss., The University of Arizona, 2000. http://hdl.handle.net/10150/289172.

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We have yet to develop a theory of explanation that will account for all of consciousness. Recent debate on this topic has been impaired because it has in large part proceeded without any explicit attention to the nature of explanation. On the one hand, the lack of commitment to any well-specified theory of explanation leads to imprecision and vagueness. On the other hand, much of the optimism concerning the possibility of explaining all aspects of consciousness stems from an attachment to the only developed theory of psychological phenomena at our disposal and the belief that all of consciousness can be captured by such a theory. Some of the inadequacy in the literature on consciousness is due to a conflation between consciousness construed as mode of presentation , that is, the way content is presented to the agent, and consciousness construed as subjective or qualitative feel. Once the two objects of concern are distinguished, we have a much clearer vision of what needs to be explained, and we can turn our focus on the proper way to do so. I argue that subjective feel is an important aspect of consciousness in need of explanation, and that an explanation of this phenomenon is distinct from an explanation of mode of presentation or representation. Furthermore, while there are well-articulated methods of explanation that properly address mode of presentation and representation, this is not the case for subjective feel. I delineate several genera of scientific explanation in an attempt to exhaust the possible methods by which we may be capable of explaining subjective feel. This involves the taxonomizing of types of phenomena that are the targets of our explanatory methods. While one type of explanatory strategy may be adequate when the target explanandum is a property, the same strategy may fall short in explaining a single event, event type, or regularity. Subjective feel is best construed as a property. However, while the method employed by cognitive science to explain mental properties may be adequate for explaining much cognitive phenomena, I argue that it is incapable of explaining subjective feel.
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Nickel, Bernhard Ph D. Massachusetts Institute of Technology. "Truth in explanation." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33711.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Linguistics and Philosophy, 2005.
Includes bibliographical references (p. 155-163).
My thesis consists of three papers on truth and explanations in science. Broadly, the question I ask is semantic. Should the best account of certain bits of our scientific practice focus on the concept of truth? More specifically, should the crucial distinctions between good and bad aspects of that practice be drawn in terms of truth? My thesis consists of three case studies: ceteris paribus laws in the special sciences, appeals to idealizations in the application of theories, and the analysis of explanations quite generally, exemplified in the asymmetry of explanation. In each case, prominent philosophers have argued that a proper treatment does not focus on truth. In each case, I argue that truth should play a central role. And in each case, the issue turns, at least in part, on the connection between the scientific practice in question and explanations.
by Bernhard Nickel.
Ph.D.
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Ooms, Renard Nicole Marie Anne. "Plato's metaphysics of explanation." Thesis, King's College London (University of London), 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324884.

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Lipton, P. "Explanation and evidence." Thesis, University of Oxford, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.371691.

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White, Roger (Roger Lewis) 1967. "Probability, explanation, and reasoning." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/8841.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Linguistics and Philosophy, 2000.
Includes bibliographical references (p. 96).
Three topics are discussed concerning the application probability and explanation to the confirmation of theories. The first concerns the debate over prediction versus accommodation. I argue that we typically have reason to be more confident of a theory given that it was constructed independently of the knowledge of certain data than if it was designed to accommodate those data. The second concerns the puzzle of the apparent 'fine-tuning' of the universe for life. I argue that the fact that our universe meets the extremely improbable yet necessary conditions for life provides no evidence for the thesis that there are, or have been, very many universes. The third chapter concerns the need to explain the existence of life. I argue that if life's existence needs an explanation at all, the place to look is in a teleological explanation. If this option is rejected, we should be content to see the origin of life as an extremely improbable fluke.
by Roger White.
Ph.D.
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Patterson, Sarah Charlotte. "Content and psychological explanation." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/13941.

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Emery, Nina R. (Nina Rebecca). "Chance, indeterminacy, and explanation." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/72921.

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Thesis (Ph. D. in Philosophy)--Massachusetts Institute of Technology, Dept. of Linguistics and Philosophy, 2012.
"June 2012." Cataloged from PDF version of thesis.
Includes bibliographical references (p. 97-101).
This thesis is about the philosophical and scientific significance of chance. Specifically, I ask whether there is a single notion of chance that both plays a well-defined scientific role and proves useful for various philosophical projects. I argue that there is, but that this notion of chance is importantly different from the one that we usually come across in the philosophical literature. In the first chapter, "Chance, Indeterminacy, and Explanation", I argue against the common and influential view that chances are those probabilities that arise when the fundamental laws are indeterministic. The problem with this view, I claim, is not that it conflicts with some antecedently plausible metaphysics of chance, but rather that it renders the distinction between chance and other sorts of probability incapable of playing any scientifically significant role. I suggest an alternative view, according to which chances are the probabilities that play a certain explanatory role-they are probabilities that explain associated frequencies. In the second chapter, "Chance, Explanation, and Measure", I build on the view that chances are the probabilities that play a certain explanatory role by developing an account of non-fundamental chances-chances that arise when the fundamental laws are deterministic. On this account, non-fundamental chances are objective measures over relevant classes of alternative possibilities. In the third chapter, "Chance and Counterfactuals", I show how the sort of chances I have argued for can play an important role in a very different sort of philosophical project. According to a number of recent arguments, one consequence of our current scientific theories is that most ordinary counterfactuals are not true. I argue that the best response to these arguments makes use of the non-fundamental chances that I have argued for in the first two chapters of the dissertation.
by Nina R. Emery.
Ph.D.in Philosophy
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Kazez, Jean Rahel. "Mental representation and causal explanation." Diss., The University of Arizona, 1990. http://hdl.handle.net/10150/185312.

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Mental causation has been a concern in the philosophy of mind since Descartes. Intuitively, thoughts are causes of behavior, and they are causes of behavior in virtue of their mental properties. The computational theory of mind views thoughts as symbol tokenings, and thus as causes. However, if the computational theory of mind is correct, the causal efficacy of mental properties is problematic. A representation tokening causes further representation tokenings or behaviors in virtue of local computational properties of the representation. Mental properties could explain mental causation as well, if they could be identified with, or they supervened upon, causally relevant computational properties of representations. But on plausible construals of the nature of mental properties, they do not. If mental properties are assigned relevance in our mental lives, the result is a picture in which the effects of mental events are overdetermined by their mental and physical properties. Since such overdetermination is implausible, the causal efficacy of mental properties should be denied. A number of philosophers have proposed sufficient conditions for causal relevance and argued that mental properties meet those conditions. The role of mental properties in laws or counterfactuals is taken to be pivotal. But there are serious problems with each of the proposed accounts. A property can play an explanatory role, even if it does not play a causal-explanatory role. The point of assigning mental properties to representations is to account for a system's information processing capacities. Mental properties can play this explanatory role without accounting for cause-effect relationships. The causal efficacy of mental properties can be denied, while an explanatory role for mental properties is maintained.
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Sutton, Peter Andrew. "Models of scientific explanation." Texas A&M University, 2005. http://hdl.handle.net/1969.1/2372.

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Ever since Hempel and Oppenheim's development of the Deductive Nomological model of scientific explanation in 1948, a great deal of philosophical energy has been dedicated to constructing a viable model of explanation that concurs both with our intuitions and with the general project of science. Here I critically examine the developments in this field of study over the last half century, and conclude that Humphreys' aleatory model is superior to its competitors. There are, however, some problems with Humphreys' account of the relative quality of an explanation, so in the end I develop and defend a modified version of the aleatory account.
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Deulofeu, Batllori Roger. "Scientific explanation in biology. Beyond mechanistic explanation." Doctoral thesis, Universitat de Barcelona, 2020. http://hdl.handle.net/10803/668748.

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Understanding how scientists explain has been one of the major goals of the philosophy of science. Given that explaining is one of the most important tasks that scientists aim at and given the high specialization that currently affects all scientific disciplines, we encounter what might at first glance appear to us as many different types of explanations and very different ways of explaining natural phenomena. This suggests a pluralist picture regarding scientific explanation, particularly in biology, namely the existence of different accounts of explanation that do not share an interesting common core. However, the main goal of the traditional analysis of scientific explanation was to elaborate a monist theory of explanation according to which all scientific explanations share a common core that makes them what they are - i.e. that they can be identified by a commonly shared set of necessary and jointly sufficient conditions. The monist accounts mainly draw on examples from physics to illustrate how this is supposed to work, leaving examples from the special science, like biology, aside. In the last twenty years, nonetheless, the rise of the New Mechanism philosophy, with its notion of mechanistic explanation, has become the dominant and widely accepted account among the philosophers of science to analyze scientific explanation in biology, challenging the pluralist view. The New mechanist account of scientific explanation is essentially monist since their defenders claim that mechanisms are all what really matters to explanation. According to mechanistic explanation, in order to explain a biological phenomenon, we have to discover the mechanism that is responsible for it. Further, we have to decompose this mechanism in order to identify its component parts and identify the causal story that connects the components with the phenomenon. Mechanistic explanations are thus considered causal explanations. The New Mechanism philosophy has arguably been very successful in analyzing how explanation works in a huge diversity of models in biology, suggesting that their account of mechanistic explanation is the only legitimate of in biology. Furthermore, New Mechanism philosophy provides a new framework that contributed to tackle traditional problems of the philosophy of science related to notions such as laws of nature, function, causation, etc. Although mechanistic explanation has proved very successful in analyzing the explanatory force of many biological models, its scope in biology is still under discussion. In the last few years, there has been voices limiting the extension of this account. On the one hand, there has been philosophers claiming that in some biological models, mathematics plays not only a representational role but an explanatory role, suggesting that those models provide explanations that rather than identifying a mechanism with its components and causal story, identify mathematical properties that are explanatory of some phenomenon. They claim that in those explanations, the system under analysis has a mathematical structure whose mathematical properties are explanatory of a particular range of explananda. On the other hand, and despite the claim widely accepted that there are no laws in biology, some philosophers claim we can still consider that some biological models explain by appeal to laws of nature, suggesting covering law accounts of scientific explanation. The present thesis dissertation is a contribution to the aforementioned debate. It provides examples of biological models whose explanatory power does not lie in its identification of mechanisms with its parts and causal story, even if the models look somehow mechanistic. I claim they provide non-mechanistic (and non-causal) explanations, in so far as the models, even if they could identify a mechanism, do not explain by pinpointing information about its causal story.
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Books on the topic "Philosophy and explanation"

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Theism and explanation. New York: Routledge, 2009.

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Ruben, David-Hillel. Explaining explanation. London: Routledge, 1990.

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The nature of explanation. New York: Oxford University Press, 1985.

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Action and its explanation. Oxford: Clarendon Press, 2003.

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Bunzel, Martin. The context of explanation. Boston: Kluwer Academic Publishers, 1993.

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Bunzl, Martin. The context of explanation. Dordrecht: Kluwer Academic Publishers, 1993.

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Gibbon, Guy E. Explanation in archaeology. Oxford, UK: Blackwell, 1989.

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Explanation and understanding. Ithaca, N.Y: Cornell University Press, 2004.

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David-Rus, Richard. Explanation and understanding through scientific models. Iași: Institutul European, 2012.

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Causality and explanation. New York: Oxford University Press, 1998.

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Book chapters on the topic "Philosophy and explanation"

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Chiao, Joan Y. "Explanation." In Philosophy of Cultural Neuroscience, 96–104. New York, NY : Routledge, 2018.: Routledge, 2017. http://dx.doi.org/10.4324/9781315148984-11.

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Lombrozo, Tania. "Explanation." In A Companion to Experimental Philosophy, 491–503. Chichester, UK: John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781118661666.ch34.

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O’Brien, Lilian. "Action Explanation." In Philosophy of Action, 77–100. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137317483_6.

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Rosenberg, Alex, and Lee McIntyre. "Scientific Explanation." In Philosophy of Science, 36–55. Fourth edition. | New York, NY : Routledge, 2020.: Routledge, 2019. http://dx.doi.org/10.4324/9780429447266-3.

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Poston, Ted. "Reasons without First Philosophy." In Reason and Explanation, 45–68. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137012265_3.

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Potochnik, Angela. "Biological Explanation." In The Philosophy of Biology, 49–65. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6537-5_3.

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Newton-Smith, W. H. "Explanation." In A Companion to the Philosophy of Science, 127–33. Oxford, UK: Blackwell Publishers Ltd, 2017. http://dx.doi.org/10.1002/9781405164481.ch19.

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Woodward, Jim. "Explanation." In The Blackwell Guide to the Philosophy of Science, 37–54. Oxford, UK: Blackwell Publishers Ltd, 2008. http://dx.doi.org/10.1002/9780470756614.ch3.

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Pitt, Joseph C. "Technological Explanation." In Philosophy of Engineering and Technology, 111–30. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0820-4_11.

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Hutto, Daniel D. "Without Explanation." In Wittgenstein and the End of Philosophy, 128–73. London: Palgrave Macmillan UK, 2003. http://dx.doi.org/10.1057/9780230503205_5.

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Conference papers on the topic "Philosophy and explanation"

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Thompson, Jessica. "Towards a common philosophy of explanation for artificial and biological intelligence." In 2018 Conference on Cognitive Computational Neuroscience. Brentwood, Tennessee, USA: Cognitive Computational Neuroscience, 2018. http://dx.doi.org/10.32470/ccn.2018.1259-0.

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Sovrano, Francesco, and Fabio Vitali. "From Philosophy to Interfaces: an Explanatory Method and a Tool Inspired by Achinstein’s Theory of Explanation." In IUI '21: 26th International Conference on Intelligent User Interfaces. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3397481.3450655.

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Premkumar, P., and S. N. Kramer. "A Generalized Expert System Shell for Implementing Mechanical Design Applications: Review, Introduction and Fundamental Concepts." In ASME 1988 Design Technology Conferences. American Society of Mechanical Engineers, 1988. http://dx.doi.org/10.1115/detc1988-0040.

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Abstract The foundations for an expert system shell for implementing mechanical design applications are presented in this paper. The shell supports facilities for knowledge acquisition, quasi-reactive planning, design evaluation, and subjective explanation. The underlying philosophy of each of these facilities and some preliminary implementation issues are discussed. A brief summary of a recent research effort and its implications on the development of a generalized expert system shell for implementing mechanical design applications are also presented.
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Sreedharan, Sarath, Alberto Olmo Hernandez, Aditya Prasad Mishra, and Subbarao Kambhampati. "Model-Free Model Reconciliation." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/83.

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Designing agents capable of explaining complex sequential decisions remains a significant open problem in human-AI interaction. Recently, there has been a lot of interest in developing approaches for generating such explanations for various decision-making paradigms. One such approach has been the idea of explanation as model-reconciliation. The framework hypothesizes that one of the common reasons for a user's confusion could be the mismatch between the user's model of the agent's task model and the model used by the agent to generate the decisions. While this is a general framework, most works that have been explicitly built on this explanatory philosophy have focused on classical planning settings where the model of user's knowledge is available in a declarative form. Our goal in this paper is to adapt the model reconciliation approach to a more general planning paradigm and discuss how such methods could be used when user models are no longer explicitly available. Specifically, we present a simple and easy to learn labeling model that can help an explainer decide what information could help achieve model reconciliation between the user and the agent with in the context of planning with MDPs.
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Tomiyama, Tetsuo, Paul Breedveld, and Herbert Birkhofer. "Teaching Creative Design by Integrating General Design Theory and the Pahl and Beitz Methodology." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28444.

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The design methodology developed by Pahl and Beitz (P&B) is one of the most widely taught design methodologies. However, this methodology is not easy to correctly exercise for non-experienced designers such as students. At TU Darmstadt in Germany, a method was developed to make students to realize the background philosophy of P&B, to reduce misunderstanding and misuse of the method, and to help them to arrive at creative design. At TU Delft in the Netherlands, an experienced designer who works on designing mechanical medical devices developed a method to generate creative designs. Although independently developed, these two methods share some commonality and have a potential to improve design education towards creative design. This paper is an attempt to give a theoretical explanation why these two methods facilitate creative design based on General Design Theory.
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Yu, Jingjun, Shouzhong Li, Shusheng Bi, and Guanghua Zong. "Symmetry Design in Flexure Systems Using Kinematic Principles." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12385.

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Inspiration for the creation of mechanical devices often comes from observing the natural structures and movements of living organisms. Understanding the wide use of modularity and compliance in nature may lead to the design of high-performance flexure systems or compliant devices. One of the most important nature-inspired paradigms for constructing flexure systems is based on the effective use of symmetry. With a rigid mathematical foundation called screw theory and Lie group. The research of this paper mainly focuses on: (i) Mathematical explanation or treatment of symmetry design wildly used in flexure systems, concerning with a series of topics such as the relationship between degree of freedom (DOF), constraint, overconstraint, decouple motion and symmetrical geometry, and How to guarantee the mobility unchanged when using symmetry design? (ii) A compliance-based analytical verification for demonstrating that the symmetry design can effectively improve accuracy and dynamic performances. (iii) The feasibility of improving accuracy performance by connecting symmetry design with the principle of elastic averaging. The whole content is organized around a case study, i.e. symmetrical design of 1-DOF translational flexure mechanisms. The results are intent to provide a rigid theoretical foundation and significant instruction for the symmetry design philosophy in flexure systems using kinematic principles.
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Silvestre, Marcus Nathan, Diego F. B. Sarzosa, and Stjin Hertelé. "A New Proposal to Obtain the CTOD Fracture Parameter for Offshore Pipeline Steels by Using Only One Clip Gage." In ASME 2020 Pressure Vessels & Piping Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/pvp2020-21232.

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Abstract The production and exploitation of oil and natural gas reserves environmentally challenging regions imposes many technological challenges related to new design requirements. Engineering Critical Assessment (ECA) is an umbrella term for complex methodologies used o assess the criticality of defects in welded structures. ECA is commonly used for oil and gas industry to derive tolerable defect sizes during installation and operation of risers. Current standardization efforts make extensive use of single edge notch tension (or SENT) specimen to reduce the level of conservatism during the assessment. A great effort has been made to evaluate CTOD as a mean to assess fracture toughness, especially for offshore structures. The double clip gage method (DCGM) is an alternative CTOD test method, which produces less conservative values comparing with J-integral conversion into CTOD. In this paper, a novel CTOD definition is developed according to the philosophy of the DCGM, but requiring a single clip gauge and providing values similar to the J-integral converted CTOD. Further details need to be validated and studied to increase the applicability of the previous proposal. So, motivated by the earlier explanation, the goal of this paper is to present a new methodology to estimate the CTOD using geometrical relationship on crack opening displacement over the crack flank.
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Aumuller, John J., and Vincent A. Carucci. "MOP, MAOP, DP and MAWP: Understanding the Differences to Avoid Unnecessary Costs." In ASME 2013 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/pvp2013-97086.

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The ASME pressure vessel and piping codes and standards provide excellent references for code writers in international jurisdictions when developing their own national codes and for safety authorities when developing regulatory acts. The inclination to customize this effort may add unnecessary complexity that unintentionally obscures the underlying engineering principles. In developing the Canadian pipeline code, the authors use the notion of maximum operating pressure or MOP similar to the MOP found in the ASME codes for pipelines. While the ASME code definitions are explicit and articulate, the MOP defined in the Canadian code is less so and has led to inadvertent confusion by industry users. Misunderstanding of complementary terminology used in ancillary ASME standards has contributed to further complexities. The use of the term, maximum allowable operating pressure or, MAOP in the ASME pipeline codes has further reduced clarity when integrating this term into international codes and regulatory acts. This paper examines, in detail, some aspects of the Canadian pipeline code and illustrates via a representative case study some of the aforementioned difficulties that have arisen. These difficulties resulted in unnecessary derating of assets by imposing operational limits that were well below actual capacity. A clear explanation of the engineering principles underlying the provisions for codes which use a “design by rules” philosophy will help operators set appropriate limits for both static and dynamic loads that may not be apparent in the specific codes considered and will be expository for regulators and code users in general.
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Дергачева, Елена, and Elena Dergacheva. "Visualizing Socio-techno-natural Processes: Issues and Challenges." In 29th International Conference on Computer Graphics, Image Processing and Computer Vision, Visualization Systems and the Virtual Environment GraphiCon'2019. Bryansk State Technical University, 2019. http://dx.doi.org/10.30987/graphicon-2019-2-168-172.

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Contemporary models and systems of data visualization, implemented on the basis of information technology, individually cover social, technological and natural processes of the world development. Modern world is developing in the conditions of transformational transitional processes, when the artificial shell, the technosphere, created by the society becomes the leading life-support system instead of the biosphere. It is a full-fledged participant in the exchange processes between a globalizing technogenic society and transforming nature, which allows us to talk about forming socio-techno-natural laws of developing the world and life. There are no integrative visual models in the world that represent evolutionary changes in three systems simultaneously – society (and man), the technosphere and the technologically transformed biosphere, on the basis of which it is possible to predict the formation of a sustainable future for humanity in connection with the expansion of socio-technonatural processes. The generally recognized visualization methodology must be supplemented by the methodology of the philosophy of the world socio-technogenic development and the change in the evolution of life for a better visual representation and explanation of the transformation processes taking place in the changing world that is becoming post-biospheric. Interdisciplinary philosophical view allows capturing the world in the integrity of its diverse characteristics and at the same time forming a problem field for visualizing transformational processes. The fundamental role of the integration link belongs to information technology, which allows us to represent visually heterogeneous data with the aim of further developing models for the safe development of mankind in the technosphere.
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Giannoni, Luca, and Marino Mazzini. "Exposure to Low Doses of Ionizing Radiation: Is the Linear No-Threshold Model Valid?" In 2014 22nd International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/icone22-30967.

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The risk assessment for population’s exposures to low doses and low dose-rates of ionizing radiation is still subject to clear uncertainties. The issue has outstanding societal importance in relation to radiologic occupational safety, medical applications of radiation, effects of the natural background radioactivity and the future of nuclear power, due to its particular influence on the public acceptance of this form of energy. This review article analyzes, in a critical, historical and bibliographical manner, the worldwide accepted hypothesis of linearity without a threshold dose (LNT model). As well known, it rejects, from its first proposal in 1946 by American geneticist and Nobel laureate Hermann J. Muller, the concept of zero-risk for exposures to any dose level of ionizing radiation. The starting point is the dose-effects relationship provided by this model and related risk’s excess graphic curve. The biological and physical motivations for the linearity assumption are argued and challenged by the explanation of human body’s natural defense mechanisms and its repair capacity of the radiation damage. Furthermore, the historical and political truthfulness of the LNT model is also contested by the review of a recent investigation by Prof. Edward Calabrese, regarding the lack of scientific sources behind Muller’s Nobel Prize Lecture. Calabrese’s inquiry demonstrates that Muller, at the moment of his declaration on LNT model’s validity, had experimental proofs contradicting his conclusions about the unacceptability of a threshold dose. This finding is of historical importance since Muller’s Nobel Lecture is a turning point in the acceptance of the linearity model in risk assessment by the major regulatory agencies till today. Finally, the results of many epidemiological and statistical studies are shown specifically. They give further evidences concerning the inapplicability of the LNT model and its overestimation of the risk for various cases of exposures to low doses of ionizing radiation in different fields. By that, hormesis model is also discussed, with its assumption of possible benefits for the organism following low dose exposures: a dose-response model characterized by low-dose stimulation and high-dose inhibition, which has been frequently observed in the aforementioned studies. The argumentations and the experimental evidences provided here challenge the validity of the LNT model. We contest the fact that its establishment is principally based on a cautionary philosophy on nuclear public safety, rather than on actual scientific comprehension of the phenomenon. As such, it implies an exaggerated conception of the radiological hazard. In particular, this article calls attention to the need for a deeper understanding of the biological impact of low doses of ionizing radiation and the development of further specific and exhaustive researches.
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