Basic and Refined Nomic Truth Approximation by Evidence-Guided Belief Set Revision

Author(s):  
Theo A. F. Kuipers
Synthese ◽  
1992 ◽  
Vol 93 (3) ◽  
pp. 299-341 ◽  
Author(s):  
Theo A. F. Kuipers
Keyword(s):  

Synthese ◽  
2014 ◽  
Vol 191 (11) ◽  
pp. 2383-2401 ◽  
Author(s):  
Gustavo Cevolani

Author(s):  
Theo A. F. Kuipers

I discuss in a systematic order the most important epistemological positions in the instrumentalism-realism debate, viz., instrumentalism, constructive empiricism, referential realism, and theory realism. My conclusions are as follows. There are good reasons for the instrumentalist to become a constructive empiricist. In turn, the constructive empiricist is forced to become a referential realist in order to give deeper explanations of success differences. Consequently, there are further good reasons for the referential realist to become a theory realist.


2020 ◽  
Vol 49 (5) ◽  
pp. 1005-1039 ◽  
Author(s):  
Sven Ove Hansson

Abstract A new formal model of belief dynamics is proposed, in which the epistemic agent has both probabilistic beliefs and full beliefs. The agent has full belief in a proposition if and only if she considers the probability that it is false to be so close to zero that she chooses to disregard that probability. She treats such a proposition as having the probability 1, but, importantly, she is still willing and able to revise that probability assignment if she receives information that gives her sufficient reasons to do so. Such a proposition is (presently) undoubted, but not undoubtable (incorrigible). In the formal model it is assigned a probability 1 − δ, where δ is an infinitesimal number. The proposed model employs probabilistic belief states that contain several underlying probability functions representing alternative probabilistic states of the world. Furthermore, a distinction is made between update and revision, in the same way as in the literature on (dichotomous) belief change. The formal properties of the model are investigated, including properties relevant for learning from experience. The set of propositions whose probabilities are infinitesimally close to 1 forms a (logically closed) belief set. Operations that change the probabilistic belief state give rise to changes in this belief set, which have much in common with traditional operations of belief change.


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