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Profile: Ryan Muldoon (University of Pennsylvania)
  1. Cyrille Imbert, Ryan Muldoon, Jan Sprenger & Kevin Zollman (2014). Introduction, SI of Synthese “The Collective Dimension of Science”. Synthese 191 (1):1-2.
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  2. Ryan Muldoon, Chiara Lisciandra, Mark Colyvan, Carlo Martini, Giacomo Sillari & Jan Sprenger (2014). Disagreement Behind the Veil of Ignorance. Philosophical Studies 170 (3):377-394.
    In this paper we argue that there is a kind of moral disagreement that survives the Rawlsian veil of ignorance. While a veil of ignorance eliminates sources of disagreement stemming from self-interest, it does not do anything to eliminate deeper sources of disagreement. These disagreements not only persist, but transform their structure once behind the veil of ignorance. We consider formal frameworks for exploring these differences in structure between interested and disinterested disagreement, and argue that consensus models offer us a (...)
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  3. Ryan Muldoon (2013). Diversity and the Division of Cognitive Labor. Philosophy Compass 8 (2):117-125.
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  4. Ryan Muldoon (2013). Evolution and Rationality: Decisions, Co-Operation and Strategic Behaviour, Samir Okasha and Ken Binmore (Eds.). Cambridge University Press, 2012, X + 281 Pages. [REVIEW] Economics and Philosophy 29 (3):425-430.
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  5. Ryan Muldoon, Chiara Lisciandra, Cristina Bicchieri, Stephan Hartmann & Jan Sprenger (2013). On the Emergence of Descriptive Norms. Politics, Philosophy and Economics 13 (1):1470594-12447791.
    A descriptive norm is a behavioral rule that individuals follow when their empirical expectations of others following the same rule are met. We aim to provide an account of the emergence of descriptive norms by first looking at a simple case, that of the standing ovation. We examine the structure of a standing ovation, and show it can be generalized to describe the emergence of a wide range of descriptive norms.
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  6. J. Christopher Hunt, Kareem Khalifa, Ryan Muldoon, Tony Smith, Michael Weisberg, Michelle G. Gibbons, Elliott O. Wagner, Andreas Wagner, Angela Potochnik & Brian McGill (2012). 1. On Ad Hoc Hypotheses On Ad Hoc Hypotheses (Pp. 1-14). Philosophy of Science 79 (1).
     
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  7. Ryan Muldoon, Michael Borgida & Michael Cuffaro (2012). The Conditions of Tolerance. Politics, Philosophy and Economics 11 (3):322-344.
    The philosophical tradition of liberal political thought has come to see tolerance as a crucial element of a liberal political order. However, while much has been made of the value of toleration, little work has been done on individual-level motivations for tolerant behavior. In this article, we seek to develop an account of the rational motivations for toleration and of where the limits of toleration lie. We first present a very simple model of rational motivations for toleration. Key to this (...)
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  8. Ryan Muldoon, Tony Smith & Michael Weisberg (2012). Segregation That No One Seeks. Philosophy of Science 79 (1):38-62.
    This paper examines a series of Schelling-like models of residential segregation, in which agents prefer to be in the minority. We demon- strate that as long as agents care about the characteristics of their wider community, they tend to end up in a segregated state. We then investigate the process that causes this, and conclude that the result hinges on the similarity of informational states amongst agents of the same type. This is quite di erent from Schelling-like behavior, and sug- gests (...)
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  9. Cristina Bicchieri & Ryan Muldoon, Social Norms.
  10. Ryan Muldoon & Michael Weisberg (2011). Robustness and Idealization in Models of Cognitive Labor. Synthese 183 (2):161-174.
  11. Michael Weisberg & Ryan Muldoon (2009). Epistemic Landscapes and the Division of Cognitive Labor. Philosophy of Science 76 (2):225-252.
    Because of its complexity, contemporary scientific research is almost always tackled by groups of scientists, each of which works in a different part of a given research domain. We believe that understanding scientific progress thus requires understanding this division of cognitive labor. To this end, we present a novel agent-based model of scientific research in which scientists divide their labor to explore an unknown epistemic landscape. Scientists aim to climb uphill in this landscape, where elevation represents the significance of the (...)
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  12. Ryan Muldoon (2007). Robust Simulations. Philosophy of Science 74 (5):873-883.
    As scientists begin to study increasingly complex questions, many have turned to computer simulation to assist in their inquiry. This methodology has been challenged by both analytic modelers and experimentalists. A primary objection of analytic modelers is that simulations are simply too complicated to perform model verification. From the experimentalist perspective it is that there is no means to demonstrate the reality of simulation. The aim of this paper is to consider objections from both of these perspectives, and to argue (...)
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