Approaching deterministic and probabilistic truth: a unified account

The basic problem of a theory of truth approximation is defining when a theory is “close to the truth” about some relevant domain. Existing accounts of truthlikeness or verisimilitude address this problem, but are usually limited to the problem of approaching a “deterministic” truth by means of deterministic theories. A general theory of truth approximation, however, should arguably cover also cases where either the relevant theories, or “the truth”, or both, are “probabilistic” in nature. As a step forward in this direction, we first present a general characterization of both deterministic and probabilistic truth approximation; then, we introduce a new account of verisimilitude which provides a simple formal framework to deal with such issue in a unified way. The connections of our account with some other proposals in the literature are also briefly discussed.

[1]  Richard Pettigrew,et al.  Accuracy and the Laws of Credence , 2016 .

[2]  Gustavo Cevolani,et al.  Verisimilitude and belief change for nomic conjunctive theories , 2012, Synthese.

[3]  David W. Miller On Distance from the Truth as a True Distance , 1979 .

[4]  Jonathan D. Nelson,et al.  Generalized Information Theory Meets Human Cognition: Introducing a Unified Framework to Model Uncertainty and Information Search , 2018, Cogn. Sci..

[5]  R. Rosenkrantz Measuring truthlikeness , 2005, Synthese.

[6]  Rudolf Carnap,et al.  Logical foundations of probability , 1951 .

[7]  Gustavo Cevolani,et al.  Verisimilitude and Belief Change for Conjunctive Theories , 2011 .

[8]  P. Kleingeld,et al.  The Stanford Encyclopedia of Philosophy , 2013 .

[9]  Ilkka Niiniluoto,et al.  Critical Scientific Realism , 1999 .

[10]  K. Fine Some Remarks on Popper’s Qualitative Criterion of Verisimilitude , 2019, Erkenntnis.

[11]  Gustavo Cevolani Truth approximation, belief merging, and peer disagreement , 2014, Synthese.

[12]  Miriam Schoenfield Accuracy and Verisimilitude: The Good, the Bad, and the Ugly , 2019 .

[13]  G. Oddie Likeness to Truth , 1986 .

[14]  T. Kuipers From Instrumentalism to Constructive Realism: On Some Relations between Confirmation, Empirical Progress, and Truth Approximation , 2000 .

[15]  James D. Laing,et al.  Prediction Analysis of Cross Classifications. , 1976 .

[16]  Roberto Festa,et al.  Optimum Inductive Methods , 1993 .

[17]  G. Brier VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITY , 1950 .

[18]  Gustavo Cevolani,et al.  A partial consequence account of truthlikeness , 2018, Synthese.

[19]  Graham Oddie The content, consequence and likeness approaches to verisimilitude: compatibility, trivialization, and underdetermination , 2011, Synthese.

[20]  Gustavo Cevolani,et al.  Truthlikeness and the Problem of Measure Sensitivity , 2017 .

[21]  Ilkka Niiniluoto,et al.  Content and Likeness Definitions of Truthlikeness , 2003 .

[22]  I. Niiniluoto Verisimilitude: The Third Period , 1998, The British Journal for the Philosophy of Science.

[23]  Roberto Festa,et al.  Verisimilitude, cross classification and prediction logic. Approaching the statistical truth by falsified qualitative theories , 2007 .

[24]  Gerhard Schurz,et al.  Zwart and Franssen’s impossibility theorem holds for possible-world-accounts but not for consequence-accounts to verisimilitude , 2010, Synthese.

[25]  G. Cevolani Approaching Truth in Conceptual Spaces , 2018, Erkenntnis.

[26]  K. Popper,et al.  Conjectures and refutations;: The growth of scientific knowledge , 1972 .

[27]  John G. Kemeny,et al.  A logical measure function , 1953, Journal of Symbolic Logic.

[28]  Vincenzo Crupi,et al.  Confirmation as partial entailment: A representation theorem in inductive logic , 2013, J. Appl. Log..

[29]  R. A. Leibler,et al.  On Information and Sufficiency , 1951 .

[30]  R. Festa On the Verisimilitude of Tendency Hypotheses , 2012 .

[31]  Wesley C. Salmon,et al.  Partial Entailment as a Basis for Inductive Logic , 1969 .

[32]  T. Kuipers Nomic Truth Approximation Revisited , 2019, Synthese Library.

[33]  G. Oddie What Accuracy Could Not Be , 2019, The British Journal for the Philosophy of Science.

[34]  William Roche Is there a place in Bayesian confirmation theory for the Reverse Matthew Effect? , 2016, Synthese.

[35]  K. Popper,et al.  Conjectures and refutations;: The growth of scientific knowledge , 1972 .