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21
Principles of Metareasoning
 Artificial Intelligence
, 1991
"... In this paper we outline a general approach to the study of metareasoning, not in the sense of explicating the semantics of explicitly specified metalevel control policies, but in the sense of providing a basis for selecting and justifying computational actions. This research contributes to a devel ..."
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Cited by 162 (10 self)
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In this paper we outline a general approach to the study of metareasoning, not in the sense of explicating the semantics of explicitly specified metalevel control policies, but in the sense of providing a basis for selecting and justifying computational actions. This research contributes to a developing attack on the problem of resourcebounded rationality, by providing a means for analysing and generating optimal computational strategies. Because reasoning about a computation without doing it necessarily involves uncertainty as to its outcome, probability and decision theory will be our main tools. We develop a general formula for the utility of computations, this utility being derived directly from the ability of computations to affect an agent's external actions. We address some philosophical difficulties that arise in specifying this formula, given our assumption of limited rationality. We also describe a methodology for applying the theory to particular problemsolving systems, a...
De Finetti Was Right: Probability Does Not Exist
, 2001
"... De Finetti's treatise on the theory of probability begins with the provocative statement PROBABILITY DOES NOT EXIST, meaning that probability does not exist in an objective sense. Rather, probability exists only subjectively within the minds of individuals. De Finetti defined subjective probabilitie ..."
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Cited by 16 (9 self)
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De Finetti's treatise on the theory of probability begins with the provocative statement PROBABILITY DOES NOT EXIST, meaning that probability does not exist in an objective sense. Rather, probability exists only subjectively within the minds of individuals. De Finetti defined subjective probabilities in terms of the rates at which individuals are willing to bet money on events, even though, in principle, such betting rates could depend on statedependent marginal utility for money as well as on beliefs. Most later authors, from Savage onward, have attempted to disentangle beliefs from values by introducing hypothetical bets whose payoffs are abstract consequences that are assumed to have stateindependent utility. In this paper, I argue that de Finetti was right all along: PROBABILITY, considered as a numerical measure of pure belief uncontaminated by attitudes toward money, does not exist. Rather, what exist are de Finetti's "previsions," or betting rates for money, otherwise known in the literature as "risk neutral probabilities." But the fact that previsions are not measures of pure belief turns out not to be problematic for statistical inference, decision analysis, or economic modeling.
Dynamic Coherence and Probability Kinematics
 Philosophy of Science
, 1987
"... you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, noncommercial use. Please contact the publisher regarding any further use of this work. Publisher contact inform ..."
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Cited by 9 (0 self)
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you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, noncommercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at.
Forthcoming in Advances in Decision Analysis: From Foundations to Applications
"... Abstract: The subjective expected utility (SEU) model rests on very strong assumptions about the consistency of decision making across a wide range of situations. The descriptive validity of these assumptions has been extensively challenged by behavioral psychologists during the last few decades, an ..."
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Cited by 6 (0 self)
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Abstract: The subjective expected utility (SEU) model rests on very strong assumptions about the consistency of decision making across a wide range of situations. The descriptive validity of these assumptions has been extensively challenged by behavioral psychologists during the last few decades, and the normative validity of the assumptions has also been reappraised by many statisticians, philosophers, and economists, motivating the development of more general utility theories and decision models. These generalized models are characterized by features such as imprecise probabilities, nonlinearly weighted probabilities, sourcedependent risk attitudes, and statedependent utilities, permitting the pattern of the decision maker’s behavior to change with the decision context and to perhaps satisfy the usual SEU assumptions only locally. Recent research in the emerging field of neuroeconomics sheds light on the physiological basis of decision making, the nature of preferences and beliefs, and interpersonal differences in decision competence. These findings do not necessarily invalidate the use of SEUbased decision analysis tools, but they suggest that care needs to be taken to structure preferences and to assess beliefs and risk attitudes in a manner that is appropriate for the decision and also for the decision maker. Key words: subjective probability, expected utility, nonexpected utility, Savage's axioms, surething
A Mistake in Dynamic Coherence Arguments
 Philosophy of Science 60
, 1993
"... you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, noncommercial use. Please contact the publisher regarding any further use of this work. Publisher contact inform ..."
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Cited by 6 (0 self)
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you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, noncommercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at.
Computers in mathematical inquiry
 in The Philosophy of Mathematical Practice
, 2008
"... Computers are playing an increasingly central role in mathematical practice. What are we to make of the new methods of inquiry? In Section 2, I survey some of the ways that computers are used in mathematics. These raise questions that seem to have a generally epistemological character, ..."
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Cited by 3 (0 self)
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Computers are playing an increasingly central role in mathematical practice. What are we to make of the new methods of inquiry? In Section 2, I survey some of the ways that computers are used in mathematics. These raise questions that seem to have a generally epistemological character,
Introductory Remarks on Metastatistics for The Practically Minded Non–Bayesian Regression Runner Contents
, 2008
"... ..."
Plausibilities of plausibilities’: an approach through circumstances. Being part I of “From ‘plausibilities of plausibilities’ to stateassignment methods” (2006), eprint arXiv:quantph/0607111
"... Probabilitylike parameters appearing in some statistical models, and their prior distributions, are reinterpreted through the notion of ‘circumstance’, a term which stands for any piece of knowledge that is useful in assigning a probability and that satisfies some additional logical properties. The ..."
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Cited by 2 (2 self)
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Probabilitylike parameters appearing in some statistical models, and their prior distributions, are reinterpreted through the notion of ‘circumstance’, a term which stands for any piece of knowledge that is useful in assigning a probability and that satisfies some additional logical properties. The idea, which can be traced to Laplace and Jaynes, is that the usual inferential reasonings about the probabilitylike parameters of a statistical model can be conceived as reasonings about equivalence classes of ‘circumstances ’ — viz., real or hypothetical pieces of knowledge, like e.g. physical hypotheses, that are useful in assigning a probability and satisfy some additional logical properties — that are uniquely indexed by the probability distributions they lead to. PACS numbers: 02.50.Cw,02.50.Tt,01.70.+w MSC numbers: 03B48,62F15,60A05 If you can’t join ’em, join ’em together. 0
A Derivation of QuasiBayesian Theory
, 1997
"... This report presents a concise and complete theory of convex sets of distributions, which extends and unifies previous approaches. Lower expectations and convex sets of probability distributions are derived from axioms of preference; concepts of conditionalization, independence and conditional indep ..."
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Cited by 1 (0 self)
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This report presents a concise and complete theory of convex sets of distributions, which extends and unifies previous approaches. Lower expectations and convex sets of probability distributions are derived from axioms of preference; concepts of conditionalization, independence and conditional independence are defined based on convex sets of distributions. c fl1996 Carnegie Mellon University This research is supported in part by NASA under Grant NAGW1175. Fabio Cozman was supported under a scholarship from CNPq, Brazil. 1 Introduction A variety of approaches for decisionmaking deal with intervalvalued inferences. Researchers have investigated the properties of inner/outer measures [19, 23, 44, 57], and lower probability [4, 9, 14, 28, 56] for evaluating and selecting courses of action; DempsterShafer theory employs belief and plausibility functions [44, 49] to represent intervalvalued "beliefs" in events. Several authors advocate the use of convex sets of distributions as a fl...
A Framework for Planning Under Uncertainty
 In Spring Symposium on Foundations of Automatic Planning, AAAI
, 1993
"... This work presents a planningparadigm# which integrates the flexibility and clearsemantics# of decision theory with search procedures providing many of the efficiency properties ofclassical# heuristic planning methods. We define plans ina# manner similar to the classical paradigm butextended# to rep ..."
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This work presents a planningparadigm# which integrates the flexibility and clearsemantics# of decision theory with search procedures providing many of the efficiency properties ofclassical# heuristic planning methods. We define plans ina# manner similar to the classical paradigm butextended# to represent nondeterministic actions, using utilities to represent goals. We then outline asearch# procedure for good plans which is guided by decision theory, and discuss knowledge representation issues from the point of view of improving decisions. Thisparadigm# puts plan choice on the same level as action choice, and has as emergent properties variants of desirable features of more classical planners, such as abstraction# and reactivity. Introduction Classical planning has developed under assumptions of a deterministic description of the effects of actions. In contrast, decision theory allows one to model problems where this assumption fails but, applied naively, leads quickly to intractabilit...