Time |
Program Title |
Presenter |
8:30-9:00 AM |
Gathering, breakfast, and introduction to the workshop |
Horacio
Arlo-Costa
(Carnegie Mellon University)
|
9:00-9:45 AM |
Decisions from Experience: The Scope and Policy of Search
In many decision-making situations, we cannot consult explicit statistics
about the risks associated with our possible actions. In lieu of
such data, we can arrive at an understanding of risky options by
sampling from them. Based on the sampled information, we then can
render a "decision from experience." One invaluable advantage of
the decision-from-experience paradigm is that it lays bare what
otherwise is often hidden: people's information search policy, both
in terms of scope and process. Studies of decisions from experience
have observed that people tend to rely on relatively small samples
from payoff distributions (frugal search). Furthermore, these studies
have revealed two prototypical search strategies: repeatedly switching
back and forth between two options versus evaluating each option
independently and transitioning only once (search policy). This
talk offers an explanation for people's frugal search and reveals
how search policies affect the ultimate decision. |
Ralph
Hertwig
(University of Basel) |
9:45-10:30 AM |
A Simple Comparative Choice Heuristic for Play in 2x2 Games
In this paper I present a simple model of strategy choice involving comparisons of payoffs across strategic options. The model implies that play may vary systematically with theoretically inconsequential changes in payoff values, predicts which equilibrium will obtain in games with multiple equilibria, predicts circumstances in which non-equilibria outcomes may predominate in certain games, predicts circumstances in which specific pure strategy outcomes will predominate in games with no pure strategy equilibria, predicts violations of iterative dominance and implies that play in games will be subject to framing effects. These predictions are tested and confirmed for five types of 2x2 games (battle of sexes games, matching games, iterative dominance games, stag-hunts, and games of pure conflict. |
Jonathan
Leland
(National Science Foundation) |
10:30-10:45 AM |
MORNING BREAK |
|
10:45-11:30 AM |
Fast and Frugal Heuristics in Perspective: Take the Best and
the Priority Heuristic in Perspective
The first part of the talk focuses on the heuristics known as Take the Best (TTB). In spite of the centrality of this heuristic in recent debates in psychology little is known about its mathematical properties. We try to fill this gap by examining the mathematical properties of the choice function it implements. We start by extending TTB beyond binary comparisons and thereupon characterizing it with respect to functional constraints. We focus on two such extensions, one in terms of maximization and another in terms of a bounded method based on successive selection from lists, as studied by Rubinstein and Salant in (2006). We offer a complete characterization of this second extension. Sometimes Gigerenzer suggests that there is a conflict between norms of rationality and his heuristics. He argues that the cognitive success of TTB and other heuristics is in a way linked to the violation of basic norms of rationality. Nevertheless the picture that emerges from our study of extensions of TTB is more nuanced and in a way conflicts with this radical view about rationality.
While TTB is concerned with fast and frugal inferences, the Priority Heuristic as proposed by Brandstatter, Gigerenzer, and Hertwig (2006) is concerned with fast and frugal decision-making.
We show that it is possible to extend the Priority Heuristic both beyond binary choice and to cases of uncertainty. We conclude with considerations about the range of applicability of the heuristics and a discussion of some objections presented in the literature (extended to the case of decisions under conditions of uncertainty).
Work done in collaboration with Horacio Arló-Costa (CMU). |
Paul Pedersen
(Carnegie Mellon University) |
11:30-12:15 PM |
Muddling Through and Making Do: Bounded Rationality and Its
Impact on How We Decide
My presentation will reflect on what we have learned about bounded
rationality since Herb Simon coined the term in 1957. I will review
the multiplicity of ways in which people have been shown to make
judgments and choices and the challenges as well as opportunities
this provides for predicting what people will decide in a given
situation and for helping people make choices they are happier with
in the long run. With attention and processing capacity in short
supply, we use local context, current state, and recent experience
to interpret information and assign importance to different subsets
of goals. This gives rise to human performance that in some areas
is unsurpassed (pattern recognition) and in other areas is frequently
regretted after the fact (impatience or procrastination). The machinery
and constraints of bounded rationality give rise to human judgment
and choice that is both adaptive and at times inconsistent
and suboptimal. I will also argue that deeper reflection on the
nature of bounded rationality can not only improve the real world
decisions of ordinary people, but also the choices made by decision
researchers about how we allocate our scarce research attention
and voice. |
Elke
Weber
(Columbia University) |
12:15-1:30PM |
LUNCH |
|
1:30-2:15 PM |
What is Quantum Cognition, and How Can It Be Used to Model
Human Judgment and Decision Behavior?
Judgment and decision making researchers face some of the same types
of puzzling problems that forced physicists to abandon classical
theory. Judgments are not simply recalled and recorded, but instead
they are constructed on line, and these judgments can be incompatible
so that the first judgment may disturb or interfere with a second.
Thus only partial information about the whole cognitive system can
be obtained at any point in time. Combining partial information
about a system into a coherent understanding of the entire system
is the hallmark of quantum theory. Quantum theory provides a fundamentally
different approach to logic, reasoning, and probabilistic inference.
In this paper, I will discuss (a) how quantum logic helps explain
why people fail to follow the distributive axiom of Boolean logic;
(b) how quantum probability helps understand why human judgments
disobey the Kolmogorov law of total probability; and (c) how quantum
theory helps predict when decision makers fail to obey the rational
axioms decision theory. |
Jerome
Busemeyer
(Indiana University at Bloomington) |
2:15-3:00 PM |
Instance-Based Learning: Integrating Decisions from Experience
in Sampling and Repeated Choice Paradigms
In decisions from experience, there are two experimental paradigms:
decisions from sampling and repeated choice. In the sampling paradigm,
people are asked to sample between two alternatives as many times
as they want, observing the outcome with no real consequences each
time, and then to select one of the two alternatives for real (i.e.,
which cause them to earn or lose money). In the repeated choice
paradigm, each selection of one of the two alternatives affects
people’s earnings and they receive immediate feedback on obtained
outcomes. These two experimental paradigms have been studied independently
and different cognitive processes have often been assumed to take
place in each of them. We argue that the two paradigms have common
cognitive processes well represented and predicted by Instance-Based
Learning Theory (IBLT). This research demonstrates that the same
cognitive model based on IBLT captures people’s risk preferences
in both paradigms better than individual models that have been created
to account for each paradigm separately. Furthermore, we demonstrate
that the model accurately predicts the sequence of sampling and
repeated choice observed in human data.
Work done in collaboration with Varun Dutt (CMU). |
Coty
Gonzalez
(Carnegie Mellon University) |
3:00-3:15 PM |
AFTERNOON BREAK |
|
3:15-4:00 PM |
Folk Choice Theory: Consequences of Gambling in a Structured
Environment
In life risk is reward. Almost always the big rewards we seek to
gain (and the big losses we seek to avoid) are relatively unlikely
to occur. This relationship between risk and return is obvious to
the financial community and to lay people alike. Nevertheless theories
of risky choice have largely ignored the impact of this relationship
on choice. During this talk, I will develop an alternative descriptive
theory of risky decision-making – folk choice theory -- that
takes as a central premise that agents have a lay understanding
of this risk/return relationship and use it to make more effective
decisions in all types of risky situations. Folk choice theory offers
a process level explanation of a range of phenomena. For instance,
in decisions made under uncertainty, folk choice theory presumes
decision makers use this risk/return relationship to infer the probability
of an outcome. This process level hypothesis offers an explanation
for several phenomena including the so-called Ellsberg paradox,
and phenomena relating to a presumed non-linear probability weighting
function. Folk choice theory also makes new testable predictions
involving how agents may learn about the likelihood of events via
the bets they are offered. Finally, I will discuss some of the methodological
implications of folk choice theory including decision science’s
over reliance on systematic designs that treat outcomes and probabilities
as independent variables that can be manipulated independent of
each other. |
Tim
Pleskac
(Michigan State University) |
4:00-4:45 PM |
Ameliorative Psychology and the Limits of Traditional Epistemology
My main goals in this presentation are to show that the standard argument
against naturalized epistemology has it almost exactly backwards,
and that Statistical Prediction Rules represent many classes of
formal methods that could supplement or replace Standard Analytic
Epistemology (SAE). SAE names a contingently clustered class of
methods and theses that have dominated English-speaking epistemology
for about the past half-century. The major contemporary theories
of SAE include versions of foundationalism (Chisholm 1981, Pollock
1974), coherentism (Bonjour 1985, Lehrer 1974), reliabilism (Dretske
1981, Goldman 1986) and contextualism (DeRose 1995, Lewis 1996).
While proponents of SAE don’t agree about how to define naturalized
epistemology, most agree that a thoroughgoing naturalism in epistemology
can’t work.
I will argue for the following five theses:
- The dominant theories of Standard Analytic Epistemology (foundationalism,
coherentism, reliabilism, contextualism) have at their core a
descriptive theory.
- This descriptive theory aims to capture the considered epistemic
judgments of a small group of idiosyncratic people.
- The standard charge leveled against naturalistic epistemology
can also be leveled against the dominant theories of Standard
Analytic Epistemology: They attempt to extract prescriptions from
descriptions.
- Some of the best psychological science of the past half-century
is deeply normative and makes specific recommendations about how
to improve our reasoning about matters of great practical significance.
- An approach to epistemology that takes seriously these psychological
findings is better suited to overcoming the is-ought gap than
are the theories of SAE.
I will then move to the positive part of the talk. Mike Bishop’s
and my work contends that our Ameliorative Psychology (partly
prompted by Simon’s work on “bounded cognition”)
is superior to SAE because it provides a motivated way of overcoming
the is-ought divide. The normative recommendations and evaluative
theses of Ameliorative Psychology can receive confirmation by
the best science of the day. And some of these recommendations
have been impressively confirmed, in the form of documented results
and a proven method for securing them. Standard Analytic Epistemology,
on the other hand, has a long tradition and the loyalty of its
enthusiasts. |
J.D.
Trout
(Loyola University- Chicago) |
4:45-5:30 PM |
Decisions from Experience in Conditions of Uncertainty
Hertwig, Barron, Weber and Erev (2004) initiated a stream of studies
where aspects of prospects are not conveyed verbally to subjects
(description) but subjects have to infer them from repeated observations
(experience). This has lead to well-known violations of prospect
theory. Hadar and Fox (2006) have argued that decisions from experience
have been misclassified as decisions under risk and proposed to
treat them as decisions under uncertainty. Therefore they have proposed
to explain the data in experience by appealing to the 'two-stage
model' of Fox and Tversky (1989) (while the usual decision weights
of Prospect Theory I explain description). The model of ambiguity
implements a form of Choquet expected utility in terms of non-additive
event-decision weights (also known as Prospect Theory II). In this
talk we report experimental results where both description and experience
should be classified as decisions under uncertainty. Although it
is very difficult (if possible at all) to find an experiential counterpart
of a vague Ellsberg urn (for the two-color problem) we appeal to
a chance set up based on double sampling determining an option that
subjects perceive as being between 'clear' and 'vague' Ellsberg
choices. This chance set-up is implementable in experience. Current
results indicate that while subjects are ambiguity averse for gains
in description (as Prospect Theory II predicts) the effect reverses
under description where subjects are ambiguity seeking. Prospect
Theory II seems unable to explain this effect. We conclude with
some hypothesis about the cause of this new asymmetry between decisions
form experience and description and by considering possible mathematical
models of the asymmetry by appealing to well known techniques in
the contemporary literature on imprecise probabilities.
Work done in collaboration with Coty Gonzalez and Varun Dutt
(CMU), and Jeff Helzner (Columbia). |
Horacio
Arlo-Costa
(Carnegie Mellon University) |