## Heuristics and normative models of judgment under uncertainty (1996)

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Venue: | International Journal of |

Citations: | 8 - 6 self |

### BibTeX

@ARTICLE{Wang96heuristicsand,

author = {Pei Wang},

title = {Heuristics and normative models of judgment under uncertainty},

journal = {International Journal of},

year = {1996}

}

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### Abstract

Psychological evidence shows that probability theoryisnotaproper descriptive model of intuitive human judgment. Instead, some heuristics have been proposed as such a descriptive model. This paper argues that probability theory has limitations even as a normative model. A new normative model of judgment under uncertainty is designed under the assumption that the system's knowledge and resources are insu cient with respect to the questions that the system needs to answer. The proposed heuristics in human reasoning can also be observed inthis new model, and can be justi ed according to the assumption.

### Citations

7052 |
Probabilistic Reasoning in Intelligent Systems
- Pearl
- 1988
(Show Context)
Citation Context ...es the correct or optimal answer, although sometimes it is not easy to apply the model. This opinion is also advocated by some authors in the study of uncertainty reasoning in artificial intelligence =-=[3, 15, 17]-=-. It is well known that the axioms of probability theory can be derived from several assumptions about the relationships between evidence and belief [5]. These assumptions, though reasonable for many ... |

2247 |
A Mathematical Theory of Evidence
- Shafer
- 1976
(Show Context)
Citation Context ...e "frequentist " [9] or "propensity" [4] interpretation. 3 ffl There are alternative normative models that compete with Pascal probability theory, such as Baconian probability [4] =-=and belief function [16]-=-. ffl Some formal descriptive models are proposed, such as information integration theory [1]. Similarly, this paper attempts to address the following questions: Is Bayesian approach always the correc... |

1186 |
Judgment under uncertainty: heuristics and biases
- Tversky, Kahneman
- 1990
(Show Context)
Citation Context ...mail: pwang@cogsci.indiana.edu International Journal of Approximate Reasoning 1994 11:1--158 c fl 1994 Elsevier Science Inc. 655 Avenue of the Americas, New York, NY 10010 0888-613X/94/$7.00s2 theory =-=[18]-=-, that is, between what we should do (according to probability theory) and what we do (according to psychological experiments). Therefore, probability theory is not a good descriptive theory for human... |

360 | A Treatise on Probability
- Keynes
- 1921
(Show Context)
Citation Context ...istribution is a useful way to express one's uncertainty about some events or propositions, it does not contain the information about the amount of evidence that supports the probability distribution =-=[13]. This type of information is -=-referred to by various authors as "ignorance", "confidence", "reliability", and so on [16, 21]. Some people argue that this information can be derived from a probability ... |

248 | Extensional Versus Intuitive Reasoning: The Conjunction Fallacy in Probability Judgment
- Tversky, Kahneman
- 1983
(Show Context)
Citation Context ...ess, is not influenced by several factors that should affect judgments of probability" [18]. The basic difference between them is that "the laws of probability derive from extensional consid=-=erations" [19], but simi-=-larity judgments are based on the sharing of properties, so they are intensional. As mentioned previously, here we need to distinguish three different meanings of "probability": 1. As a pure... |

162 |
Probability, Frequency, and Reasonable Expectation
- Cox
- 1946
(Show Context)
Citation Context ...ns that happen in human thinking, for the following reasons: 1. Probability theory has a solid foundation. Its conclusions are derived deductively from a set of intuitive, or even self-evident axioms =-=[5]-=-. 2. Most of the people who make the fallacy are disposed, after explanation, to accept that they made a mistake [19]. As a result, the research activities in this domain often consist of the followin... |

106 | How to make cognitive illusions disappear: Beyond â€˜heuristics and biases
- Gigerenzer
- 1991
(Show Context)
Citation Context ...t of the people who make the fallacy are disposed, after explanation, to accept that they made a mistake [19]. As a result, the research activities in this domain often consist of the following steps =-=[9, 12]-=-: 1. To identify the problem by carrying out psychological experiments, and compare the results with the conclusions of probability theory; 2. To explain the result by looking for the heuristics that ... |

93 |
Good Thinking: The Foundations of Probability and Its Applications
- Good
- 1983
(Show Context)
Citation Context ...ledge [21]. It is true that when applied into a practical domain, NARS may produce wrong expectations, but so does probability theory. NARS is not proposed to replace Bayesian models. In Good's terms =-=[10], Bayesian approach -=-is toward a "Type I" rationality by maximizing the expected utility, while NARS is toward a "Type II" rationality where the cost of computing must be taken into account. If Bayesia... |

85 |
Knowing with certainty: The appropriateness of extreme confidence
- Fischhoff, Slovic, et al.
- 1977
(Show Context)
Citation Context ... more evidence one has collected, the more confident one feels when making a judgment on the issue, though it does not follow that the judgment become "truer" or "more accurate" in=-= an objective sense [7, 8]-=-. For a detailed discussion of the related semantics issues, see [22]. 3.3. Inference rules In NARS there are two types of rules, one is for new judgments derivation (including deduction, induction, a... |

80 | defense of probability
- In
- 1985
(Show Context)
Citation Context ...es the correct or optimal answer, although sometimes it is not easy to apply the model. This opinion is also advocated by some authors in the study of uncertainty reasoning in artificial intelligence =-=[3, 15, 17]-=-. It is well known that the axioms of probability theory can be derived from several assumptions about the relationships between evidence and belief [5]. These assumptions, though reasonable for many ... |

72 |
Can human irrationality be experimentally demonstrated
- Cohen
- 1981
(Show Context)
Citation Context ...ssed above, there are opinions to explain the discrepancy as a challenge to Bayesian approach: ffl Probability theory can be interpreted differently, such as in the "frequentist " [9] or &qu=-=ot;propensity" [4]-=- interpretation. 3 ffl There are alternative normative models that compete with Pascal probability theory, such as Baconian probability [4] and belief function [16]. ffl Some formal descriptive models... |

60 |
Confidence in judgment: persistence of the illusion of validity
- Einhorn, Hogarth
- 1978
(Show Context)
Citation Context ... more evidence one has collected, the more confident one feels when making a judgment on the issue, though it does not follow that the judgment become "truer" or "more accurate" in=-= an objective sense [7, 8]-=-. For a detailed discussion of the related semantics issues, see [22]. 3.3. Inference rules In NARS there are two types of rules, one is for new judgments derivation (including deduction, induction, a... |

51 |
On the study of statistical intuitions
- Kahneman, Tversky
- 1982
(Show Context)
Citation Context ...t of the people who make the fallacy are disposed, after explanation, to accept that they made a mistake [19]. As a result, the research activities in this domain often consist of the following steps =-=[9, 12]-=-: 1. To identify the problem by carrying out psychological experiments, and compare the results with the conclusions of probability theory; 2. To explain the result by looking for the heuristics that ... |

42 |
Beyond discrete biases: Functional and dysfunctional aspects of judgmental heuristics
- Hogarth
- 1981
(Show Context)
Citation Context ...cy, though looks reasonable, is not always satisfiable, for the following reasons: 1. When a system is open to new evidence, that is, the system works in a continuous, incremental, or adaptive manner =-=[11]-=-, it is always possible for new knowledge to conflict with previous knowledge. 2. Under a time pressure, it is often impossible for the system to locate and consider all relevant knowledge when a judg... |

36 |
Costs and Benefits of Judgment Errors: Implications for Debiasing
- Arkes
- 1991
(Show Context)
Citation Context ...ed by several factors, such as relevance, importance, usefulness, and so on. Therefore, it is not surprising that certain events, like priming and association, influence the availability distribution =-=[2]-=-. Because which piece of knowledge to use at each step of reasoning is determined by the current context (by priming) and past experience (by association), it is inevitable that some knowledge, necess... |

33 | From Inheritance Relation to Non-Axiomatic Logic. International Journal of Approximate Reasoning 7, 1 74
- Wang
- 1994
(Show Context)
Citation Context ...rmation about the amount of evidence that supports the probability distribution [13]. This type of information is referred to by various authors as "ignorance", "confidence", "=-=;reliability", and so on [16, 21]-=-. Some people argue that this information can be derived from a probability distribution [15, 17], but this argument is invalid, because it is actually based on a confusion between the background know... |

33 | Non-Axiomatic Reasoning System: Exploring the Essence of Intelligence
- Wang
- 1995
(Show Context)
Citation Context ... This paper is a follow-up of [21], and its purpose is to show some implications of the formal model defined in the previous paper. For a more recent and complete description of the NARS project, see =-=[23]-=-. Though the above discussions only address some, but not all, aspects of the system, we can still get some conclusions about the models of judgment under uncertainty. Despite the fact that NARS is de... |

21 | Belief revision in probability theory
- Wang
- 1993
(Show Context)
Citation Context ...und knowledge that supports a probability assignment and the proposition that appears within a conditional probability assignment as the condition. A detailed discussion on this issue can be found in =-=[20]-=-. In the following, we will summarize the argument briefly. Suppose we are talking about the uncertainty of the propositions in a space S. For this purpose, we collect some background knowledge C, and... |

13 |
Dominance of accuracy information and neglect of base rates in probability estimation
- Lyon, Slovic
- 1976
(Show Context)
Citation Context ...aws of probability do not apply to all variants of uncertainty with equal force." [12] Some authors even take such a radical position by claiming that "the world operates according to Bayes'=-= Theorem" [14]-=-. According to this opinion, Bayesian approach is the normative model for judgment under uncertainty, and it always gives the correct or optimal answer, although sometimes it is not easy to apply the ... |

11 |
Updating with belief functions, ordinal conditional functions and possibility measures. Uncertainty in
- Dubois, Prade
- 1991
(Show Context)
Citation Context ...t on a proposition, whereas the previous probability assignment on the proposition is completely ignored. As a result, updating is asymmetric, but revision (or evidence combination [16]) is symmetric =-=[6]-=-. Although updating is a valid operation, it cannot be used to replace revision. 2.3. Extensional interpretation Probability theory is traditional interpreted in an extensional way [19], which means t... |

10 |
A statistical view of uncertainty in expert systems
- Spiegelhalter
- 1986
(Show Context)
Citation Context ...es the correct or optimal answer, although sometimes it is not easy to apply the model. This opinion is also advocated by some authors in the study of uncertainty reasoning in artificial intelligence =-=[3, 15, 17]-=-. It is well known that the axioms of probability theory can be derived from several assumptions about the relationships between evidence and belief [5]. These assumptions, though reasonable for many ... |

7 |
A cognitive theory of judgment and decision
- Anderson
- 1986
(Show Context)
Citation Context ... models that compete with Pascal probability theory, such as Baconian probability [4] and belief function [16]. ffl Some formal descriptive models are proposed, such as information integration theory =-=[1]-=-. Similarly, this paper attempts to address the following questions: Is Bayesian approach always the correct model to use? If not, when and why? Are there other normative models for reasoning under un... |

7 | Reference classes and multiple inheritances
- Wang
- 1995
(Show Context)
Citation Context ...here a is an object and B is a set, is often determined via another set R, the "reference class". When "a 2 R" is true and the probability of "R ae B" is known, this valu=-=e can be inherited by "a 2 B" [24]-=-. Though this is a very useful and reasonable way to apply probability theory to everyday life, we should keep the following points in mind. First, this is a way to interpret probability, but not nece... |

6 |
Knowing with Certainty: The Appropriateness of Extreme Con dence
- Baruch, Lichtenstein
(Show Context)
Citation Context ...e more evidence one has collected, the more con dent one feels when making a judgment on the issue, though it does not follow that the judgment become \truer" or \more accurate" in an objective sense =-=[7, 8]-=-. For a detailed discussion of the related semantics issues, see [22]. 3.3. Inference rules In NARS there are twotypes of rules, one is for new judgments derivation (including deduction, induction, ab... |

5 | Grounded on experience: Semantics for intelligence
- Wang
- 1995
(Show Context)
Citation Context ...pt to equally treat extension and intension. When the uncertainty of a judgment is determined, both the extensional factor (shared instances) and intensional factor (shared properties) are considered =-=[21, 22]-=-. By doing this, it does not mean that they are not different, but that their effects are the same in the judgment. It is valid to build normative theories to process extension or intension separately... |

3 |
Con dence in judgment: persistence of illusion of validity
- Einhorn, Hogarth
- 1978
(Show Context)
Citation Context ...e more evidence one has collected, the more con dent one feels when making a judgment on the issue, though it does not follow that the judgment become \truer" or \more accurate" in an objective sense =-=[7, 8]-=-. For a detailed discussion of the related semantics issues, see [22]. 3.3. Inference rules In NARS there are twotypes of rules, one is for new judgments derivation (including deduction, induction, ab... |

1 |
Costa and bene ts of judgment errors: implications for debiasing
- Arkes
- 1991
(Show Context)
Citation Context ...ned by several factors, such as relevance, importance, usefulness, and so on. Therefore, it is not surprising that certain events, like priming and association, in uence the availability distribution =-=[2]-=-. Because which piece of knowledge to use at each step of reasoning is determined by the current context (by priming) and past experience (by association), it is inevitable that some knowledge, necess... |