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Borut Trpin
Ludwig Maximilians Universität, München
  1.  68
    Inference to the Best Explanation in Uncertain Evidential Situations.Borut Trpin & Max Pellert - 2019 - British Journal for the Philosophy of Science 70 (4):977-1001.
    It has recently been argued that a non-Bayesian probabilistic version of inference to the best explanation (IBE*) has a number of advantages over Bayesian conditionalization (Douven [2013]; Douven and Wenmackers [2017]). We investigate how IBE* could be generalized to uncertain evidential situations and formulate a novel updating rule IBE**. We then inspect how it performs in comparison to its Bayesian counterpart, Jeffrey conditionalization (JC), in a number of simulations where two agents, each updating by IBE** and JC, respectively, try to (...)
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  2.  11
    Lying, more or less: a computer simulation study of graded lies and trust dynamics.Borut Trpin, Anna Dobrosovestnova & Sebastian J. Götzendorfer - 2020 - Synthese 199 (1-2):1-28.
    Partial lying denotes the cases where we partially believe something to be false but nevertheless assert it with the intent to deceive the addressee. We investigate how the severity of partial lying may be determined and how partial lies can be classified. We also study how much epistemic damage an agent suffers depending on the level of trust that she invests in the liar and the severity of the lies she is told. Our analysis is based on the results from (...)
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  3. Influence of Conditionals on Belief Updating.Borut Trpin - 2018 - Dissertation, University of Ljubljana
    This doctoral dissertation investigates what influence indicative conditionals have on belief updating and how learning from conditionals may be modelled in a probabilistic framework. Because the problem is related to the interpretation of conditionals, we first assess different semantics of indicative conditionals. We propose that conditionals should be taken as primary concepts. This allows us to defend a claim that learning a conditional is equivalent to learning that the relevant conditional probability is 1. This implies that learning a conditional can (...)
     
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  4. Jeffrey conditionalization: proceed with caution.Borut Trpin - 2020 - Philosophical Studies 177 (10):2985-3012.
    It has been argued that if the rigidity condition is satisfied, a rational agent operating with uncertain evidence should update her subjective probabilities by Jeffrey conditionalization or else a series of bets resulting in a sure loss could be made against her. We show, however, that even if the rigidity condition is satisfied, it is not always safe to update probability distributions by JC because there exist such sequences of non-misleading uncertain observations where it may be foreseen that an agent (...)
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  5.  33
    Corrigendum To: Inference to the Best Explanation in Uncertain Evidential Situations.Borut Trpin & Max Pellert - 2021 - British Journal for the Philosophy of Science 72 (1):355-355.
    Brit. J. Phil. Sci. 0, 1–25. Published 14 March 2018.
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  6.  14
    Against Methodological Gambling.Borut Trpin - forthcoming - Erkenntnis:1-21.
    Should a scientist rely on methodological triangulation? Heesen et al. (Synthese 196(8):3067–3081, 2019) recently provided a convincing affirmative answer. However, their approach requires belief gambles if the evidence is discordant. We instead propose epistemically modest triangulation (EMT), according to which one should withhold judgement in such cases. We show that for a scientist in a methodologically diffident situation the expected utility of EMT is greater than that of Heesen et al.’s (2019) triangulation or that of using a single method. We (...)
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  7.  31
    ‘Seize It, If Thou Dar’St’: Three Types of Imperative Conditional in Richard II.Borut Trpin - 2019 - In Craig Bourne & Emily Caddick Bourne (eds.), The Routledge Companion to Shakespeare and Philosophy. Routledge.
    Characters in Richard II utter a number of neglected, yet philosophically interesting imperative conditionals. Based on a close reading of these examples, I provide a tripartite typology of imperative conditionals. The type 1 constitute the class of standard imperative conditionals; the type 2 implicate that the antecedent is false; and the type 3 implicate that the command in the consequent is to be complied with. I show how the type 2 and type 3 conditionals can be identified, and explain when (...)
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  8. What is Learned From Conditionals?Borut Trpin - 2015 - Balkan Journal of Philosophy 7 (2):125-136.
    Some of the information that we learn comes to us in a conditional form. This has proven to be a problem for philosophers, who try to explain how probabilistic beliefs change when one learns from conditional sentences. The problem is that a straight-forward solution is not possible: the partial belief in the antecedent and the partial belief in the consequent either increase, decrease, or remain the same. Two existing approaches to learning from indicative conditionals are considered: an explanatory one, and (...)
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  9.  1
    Bayesians Still Don’T Learn From Conditionals.Mario Günther & Borut Trpin - forthcoming - Acta Analytica:1-13.
    One of the open questions in Bayesian epistemology is how to rationally learn from indicative conditionals. Eva et al. :461–508, 2020) propose a strategy to resolve this question. They claim that their strategy provides a “uniquely rational response to any given learning scenario”. We show that their updating strategy is neither very general nor always rational. Even worse, we generalize their strategy and show that it still fails. Bad news for the Bayesians.
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  10.  4
    Conference Report: The Third Conference of the East European Network for Philosophy of Science (EENPS 2021), 9–11 June, 2021. [REVIEW]Borut Trpin - 2021 - Kriterion – Journal of Philosophy 35 (2):191-195.
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