G. Shafer

Publications226
h-index42
Citations22,200
Highly Influential Citations2,119
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A mathematical theory of evidence
TLDR
This book develops an alternative to the additive set functions and the rule of conditioning of the Bayesian theory: set functions that need only be what Choquet called "monotone of order of infinity." and Dempster's rule for combining such set functions. Expand
Axioms for probability and belief-function proagation
TLDR
This paper describes an abstract framework and axioms under which exact local computation of marginals is possible and shows how the problem of computing marginals of joint probability distributions and joint belief functions fits the general framework. Expand
Probability and Finance: It's Only a Game!
Preface. Probability and Finance as a Game. PROBABILITY WITHOUT MEASURE. The Historical Context. The Bounded Strong Law of Large Numbers. Kolmogorov's Strong Law of Large Numbers. The Law of the… Expand
A tutorial on conformal prediction
TLDR
This tutorial presents a self-contained account of the theory of conformal prediction and works through several numerical examples of how the model under which successive examples are sampled independently from the same distribution can be applied to any method for producing ŷ. Expand
The art of causal conjecture
TLDR
The Art of Causal Conjecture shows that causal ideas can be equally important in theory and by bringing causal ideas into the foundations of probability allows causal conjectures to be more clearly quantified, debated, and confronted by statistical evidence. Expand
Algorithmic Learning in a Random World
Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness. Based on… Expand
Probability propagation
TLDR
The account given here avoids the divisions required by conditional probabilities and generalizes readily to alternative measures of subjective probability, such as Dempster-Shafer or Spohnian belief functions. Expand
Perspectives on the theory and practice of belief functions
  • G. Shafer
  • Mathematics, Computer Science
  • Int. J. Approx. Reason.
  • 1 September 1990
TLDR
The place of belief functions within the broader topic of probability and the place of probability within the larger set of formalisms used by artificial intelligence are considered. Expand
Readings in Uncertain Reasoning
TLDR
This volume collects 42 key papers from the literature addressing the methods that have been used in artificial intelligence to build systems with the ability to manage uncertainty. Expand
The Enterprise of Knowledge: An Essay on Knowledge, Credal Probability, and Chance
This book presents a major conceptual and speculative philosophic investigation of knowledge, belief, and decision. It offers a distinctive approach to the improvement of knowledge where knowledge is… Expand
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