Normality and actual causal strength Icard, Thomas F.; Kominsky, Jonathan F.; Knobe, Joshua
Cognition,
April 2017, 2017-04-00, 20170401, Letnik:
161
Journal Article
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Existing research suggests that people’s judgments of actual causation can be influenced by the degree to which they regard certain events as normal. We develop an explanation for this phenomenon ...that draws on standard tools from the literature on graphical causal models and, in particular, on the idea of probabilistic sampling. Using these tools, we propose a new measure of actual causal strength. This measure accurately captures three effects of normality on causal judgment that have been observed in existing studies. More importantly, the measure predicts a new effect (“abnormal deflation”). Two studies show that people’s judgments do, in fact, show this new effect. Taken together, the patterns of people’s causal judgments thereby provide support for the proposed explanation.
While Bayesian models have been applied to an impressive range of cognitive phenomena, methodological challenges have been leveled concerning their role in the program of rational analysis. The focus ...of the current article is on computational impediments to probabilistic inference and related puzzles about empirical confirmation of these models. The proposal is to rethink the role of Bayesian methods in rational analysis, to adopt an independently motivated notion of rationality appropriate for computationally bounded agents, and to explore broad conditions under which (approximately) Bayesian agents would be rational. The proposal is illustrated with a characterization of costs inspired by thermodynamics.
Existing research has shown that norm violations influence causal judg- ments, and a number of different models have been developed to explain these effects. One such model, the necessity/sufficiency ...model, predicts an interac- tion pattern in people's judgments. Specifically, it predicts that when people are judging the degree to which a particular factor is a cause, there should be an interaction between (a) the degree to which that factor violates a norm and (b) the degree to which another factor in the situation violates norms. A study of moral norms (N=1000) and norms of proper functioning (N=3000) revealed robust evidence for the predicted interaction effect. The implications of these patterns for existing theories of causal judgments is discussed.
While pragmatic arguments for numerical probability axioms have received much attention, justifications for axioms of qualitative probability have been less discussed. We offer an argument for the ...requirement that an agent’s qualitative (comparative) judgments be probabilistically representable, inspired by, but importantly different from, the Money Pump argument for transitivity of preference and Dutch book arguments for quantitative coherence. The argument is supported by a theorem, to the effect that a subject is systematically susceptible to dominance given her preferred acts, if and only if the subject’s comparative judgments preclude representation by a standard probability measure (or set of such measures).
When several causes contributed to an outcome, people often single out one as "the" cause. What explains this selection? Previous work has argued that people select abnormal events as causes, though ...recent work has shown that sometimes normal events are preferred over abnormal ones. Existing studies have relied on vignettes that commonly feature agents committing immoral acts. An important challenge to the thesis that norms permeate causal reasoning is that people's responses may merely reflect pragmatic or social reasoning rather than arising from causal cognition per se. We tested this hypothesis by asking whether the previously observed patterns of causal selection emerge in tasks that recruit participants' causal reasoning about physical systems. Strikingly, we found that the same patterns observed in vignette studies with intentional agents arise in visual animations of physical interactions. Our results demonstrate how deeply normative expectations affect causal cognition.
Why Be Random? Icard, Thomas
Mind,
06/2021, Letnik:
130, Številka:
517
Journal Article
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Abstract
When does it make sense to act randomly? A persuasive argument from Bayesian decision theory legitimizes randomization essentially only in tie-breaking situations. Rational behaviour in ...humans, non-human animals, and artificial agents, however, often seems indeterminate, even random. Moreover, rationales for randomized acts have been offered in a number of disciplines, including game theory, experimental design, and machine learning. A common way of accommodating some of these observations is by appeal to a decision-maker’s bounded computational resources. Making this suggestion both precise and compelling is surprisingly difficult. Toward this end, I propose two fundamental rationales for randomization, drawing upon diverse ideas and results from the wider theory of computation. The first unifies common intuitions in favour of randomization from the aforementioned disciplines. The second introduces a deep connection between randomization and memory: access to a randomizing device is provably helpful for an agent burdened with a finite memory. Aside from fit with ordinary intuitions about rational action, the two rationales also make sense of empirical observations in the biological world. Indeed, random behaviour emerges more or less where it should, according to the proposal.
Logics of imprecise comparative probability Ding, Yifeng; Holliday, Wesley H.; Icard, Thomas F.
International journal of approximate reasoning,
20/May , Letnik:
132
Journal Article
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This paper studies connections between two alternatives to the standard probability calculus for representing and reasoning about uncertainty: imprecise probability and comparative probability. The ...goal is to identify complete logics for reasoning about uncertainty in a comparative probabilistic language whose semantics is given in terms of imprecise probability. Comparative probability operators are interpreted as quantifying over a set of probability measures. Modal and dynamic operators are added for reasoning about epistemic possibility and updating sets of probability measures.
We prove that the generalized cancellation axiom for incomplete comparative probability relations introduced by Ríos Insua (Theory Decis 33:83–100,
1992
) and Alon and Lehrer (J Econ Theory ...151:476–492,
2014
) is stronger than the standard cancellation axiom for complete comparative probability relations introduced by Scott (J Math Psychol 1:233–247,
1964
), relative to their other axioms for comparative probability in both the finite and infinite cases. This result has been suggested but not proved in the previous literature.
Inferring probability comparisons Harrison-Trainor, Matthew; Holliday, Wesley H.; Icard, Thomas F.
Mathematical social sciences,
January 2018, 2018-01-00, 20180101, Letnik:
91
Journal Article
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The problem of inferring probability comparisons between events from an initial set of comparisons arises in several contexts, ranging from decision theory to artificial intelligence to formal ...semantics. In this paper, we treat the problem as follows: beginning with a binary relation ≿ on events that does not preclude a probabilistic interpretation, in the sense that ≿ has extensions that are probabilistically representable, we characterize the extension ≿+ of ≿ that is exactly the intersection of all probabilistically representable extensions of ≿. This extension ≿+ gives us all the additional comparisons that we are entitled to infer from ≿, based on the assumption that there is some probability measure of which ≿ gives us partial qualitative information. We pay special attention to the problem of extending an order on states to an order on events. In addition to the probabilistic interpretation, this problem has a more general interpretation involving measurement of any additive quantity: e.g., given comparisons between the weights of individual objects, what comparisons between the weights of groups of objects can we infer?
•A characterization is given of the least extension of an ordering on subsets of a finite set that is representable by a collection of probability measures.•Special attention is paid to the problem of extending an ordering on elements of a set to an ordering on its powerset.•Examples are given of applications to decision making and general measurement of additive quantities.
We present a formal system for reasoning about inclusion and exclusion in natural language, following work by MacCartney and Manning. In particular, we show that an extension of the Monotonicity ...Calculus, augmented by six new type markings, is sufficient to derive novel inferences beyond monotonicity reasoning, and moreover gives rise to an interesting logic of its own. We prove soundness of the resulting calculus and discuss further logical and linguistic issues, including a new connection to the classes of weak, strong, and superstrong negative polarity items.
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