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Revising Probabilistic Prolog Programs
[chapter]
2007
Lecture Notes in Computer Science
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Here, we define and study the problem of revising ProbLog theories from examples. ...
In a recently submitted paper [1], the ProbLog (probabilistic prolog) language has been introduced and various algorithms have been developed for solving and approximating ProbLog queries. ...
Conclusion We have introduced a new type of theory revision problem involving probabilistic theories and sketched an algorithm for solving it. ...
doi:10.1007/978-3-540-73847-3_7
fatcat:eawkno5nxvgvhiozhjte3pdaiu
On the use of stochastic local search techniques to revise first-order logic theories from examples
2016
Machine Learning
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Theory Revision from Examples is the process of repairing incorrect theories and/or improving incomplete theories from a set of examples. ...
This process usually results in more accurate and comprehensible theories than purely inductive learning. ...
We would like to thank all the authors of previous work that made their systems and datasets publicly available. ...
doi:10.1007/s10994-016-5595-3
fatcat:ofvixddaxnethgytnd4t67gkhu
Introduction to the special issue "Beliefs in Groups" of Theory and Decision
2018
Theory and Decision
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fourth contribution, and qualitative probabilities ('probability grades') in the fifth contribution. ...
This symposium in the overlap of philosophy and decision theory is described well by its title "Beliefs in Groups". Each word in the title matters, with one intended ambiguity. ...
Compliance with ethical standards Funding Funding was provided by Agence Nationale de la Recherche (ANR) and Deutsche Forschungsgemeinschaft (DFG) (ColAForm). ...
doi:10.1007/s11238-018-9654-z
fatcat:3c5dpsop5jdqrlmtkekkenlwea
When is an Example a Counterexample?
[article]
2013
arXiv
pre-print
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We suggest that the example is better seen as a failure to apply the theory of belief revision in sufficient detail. ...
The main contribution is conceptual aiming at the literature on the philosophical foundations of the AGM theory of belief revision [1]. ...
The key step is to forge a connection between the AGM theory of belief revision and nonstandard probability measures. ...
arXiv:1310.6432v1
fatcat:hnbtyhbc4zfbpjnmmnq3llw3w4
The Probability of a Possibility: Adding Uncertainty to Default Rules
[chapter]
1993
Uncertainty in Artificial Intelligence
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We also show how our system can be viewed as a unification of probability theory and possi bility theory, highlighting their orthogonality and providing a means for expressing the probability of a possibility ...
Thus, our system accounts for the best properties of qualitative methods of update (in particular, the AGM theory of revision) and probabilistic meth ods. ...
In this sense, our logic is a unification of probability theory and possibility theory that highlights their orthogonality and adds to possibility theory the means to express the probability of a possibility ...
doi:10.1016/b978-1-4832-1451-1.50060-3
fatcat:2s23ivvf55grxau7g3fwsqujhi
Is the mind Bayesian? The case for agnosticism
2006
Mind & Society
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They regard (i) the background of revision (the Bayesian model considers only revising situations but not updating situations), and (ii) the notorious case of the null priors. ...
for it to be the basis of a probability judgment by individual participants. ...
Acknowledgments The authors thank Denis Hilton, David Over and Steve Sloman for their comments on various drafts of this paper. ...
doi:10.1007/s11299-006-0007-1
fatcat:y6ppplqkpjg7tlhwpixsdihntu
MODELING PARTIAL IGNORANCE IN ARTIFICAL INTELLIGENCE APPLICATIONS
2005
Environment Technology Resources Proceedings of the International Scientific and Practical Conference
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This study aims to extend and deepen a survey of modern extensions of probability theory represented in [6, 7]. ...
The classical probability theory possesses rather limited possibilities and cannot cope with situations of partial ignorance. Other approaches are required allowing one to solve tasks of that kind. ...
In probability theory, both G-revision and F-revision are implemented by means of Bayes' theorem. ...
doi:10.17770/etr2005vol1.2151
fatcat:3kqynm2tefa6zfy4apb3uqdahq
Paradigms, possibilities, and probabilities: Comment on Hinterecker, Knauff, and Johnson-Laird (2016)
2019
Journal of Experimental Psychology. Learning, Memory and Cognition
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Hinterecker, Knauff, and Johnson-Laird (2016) compared the adequacy of the probabilistic new paradigm in reasoning with the recent revision of mental models theory (MMT) for explaining a novel class of ...
It is also argued that the revision of MMT is not well motivated and its adoption leads to many logical absurdities. ...
No computational level theory of revised MMT. ...
doi:10.1037/xlm0000586
pmid:30688496
fatcat:pxcq7zmhxbdrled4i5pw3mnbou
Page 1044 of The American Economic Review Vol. 40, Issue 5
[page]
1950
The American Economic Review
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; and up to date information on the United Nations and the International Trade Organization. probably 704 pp. $425
MONEY AND BANKING, Revised Raymond P. ...
Kent, Univ. of Notre Dame
As in the original edition, this revision maintains a balance between the discussion of monetary and banking theory, and the description of banking institutions. ...
Taking Advantage of Difference in Opinion
2006
Episteme: A journal of individual and social epistemology
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In particular, it argues that rational individual revision of opinion implies that aggregation problems are unstable in a certain sense and that solving them by exploiting the information embedded in individual ...
ABSTRACTDiversity of opinion both presents problems and affords opportunities. Differences of opinion can stand in the way of reaching an agreement within a group on what decisions to take. ...
Answers to this question are given by theories of revision: Bayesian conditioning models for probability revision are perhaps the best known -see Joyce [11] -but there are also well developed theories ...
doi:10.3366/epi.2006.3.3.141
fatcat:puywwf37ifazlhvvjn72dka7q4
Probability and statistics: 5 questions
2010
ChoiceReviews
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How do you conceive of the relationship between probability theory and/or statistics and other disciplines? ...
What do you consider the most neglected topics and/or contributions in probability theory and/or statistics? ...
doi:10.5860/choice.47-5706
fatcat:l4wi5ghmcnc65k6kja7l2gebtu
Revising de Broglie-Bohm trajectories' momentum distribution
[article]
2022
arXiv
pre-print
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For this purpose, we use the de Broglie-Bohm theory and the revised theory. The results are compared in position and in momentum space. ...
This is not fulfilled by either the de Broglie-Bohm theory or the revised theory. ...
arXiv:2201.05971v1
fatcat:tt6rtw6nvjc7ppr7zmqoafnxv4
Bias-Driven Revision of Logical Domain Theories
1994
The Journal of Artificial Intelligence Research
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The theory revision problem is the problem of how best to go about revising a deficient domain theory using information contained in examples that expose inaccuracies. ...
PTR is proved to converge to a theory which correctly classifies all examples, and shown experimentally to be fast and accurate even for deep theories. ...
The authors also wish to thank the JAIR reviewers for their exceptionally prompt and helpful remarks. ...
doi:10.1613/jair.27
fatcat:dg72tshzjrakvkzvd3dqcbgaqy
Heuristics and normative models of judgment under uncertainty
1996
International Journal of Approximate Reasoning
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This paper argues that probability theory has limitations even as a normatiue model. ...
KEYWORDS: subjective probability, normative and descriptive models, heuristics and bias, insufficient knowledge and resources, nonaxiomatic reasoning system. ...
do (according to probability theory) and what we do (according to psychological experiments). ...
doi:10.1016/0888-613x(95)00091-t
fatcat:t4etiifnljb3pdvlmcnz5nivse
Page 10 of Mathematical Reviews Vol. , Issue 90I
[page]
1990
Mathematical Reviews
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In the probabilistic case, belief states are modelled by probability functions and belief revision (or, better, probability revision) by mappings from probability functions to probability functions. ...
if, for some P in P, A=t(P) and B = t(P*x), where P is the set of all possible probability functions, ¢(P) is the “top” of P and * is a probability revision operation. ...
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