Decision Theory Stanford Encyclopedia of Philosophy
Furthermore it is possible to relax the assumptions of perfect information, rationality and so forth in various ways, and produce a series of different prescriptions or predictions about behaviour, allowing for further tests of the kind of decision-making that occurs in practice. A particular equilibrium pattern might be improved, for most or even all drivers, if they could all shift simultaneously to another pattern, but no driver has a motive to shift pattern without changes by the others; satisfaction of the conditions for a Nash equilibrium guarantees only a local optimum. In particular, it is not generally possible to reach global optima by market forces alone without auxiliary processes and institutions that coordinate individual behaviors to avoid inferior local optima. However, when decisions are too complicated or too emotional, people may avoid decision making or find themselves paralyzed by the process. There are often numerous potential trajectories of advanced cancer that are difficult to predict.
In their framework, preferences
satisfying some minimal constraints are representable as dependent on
the bundle of properties in terms of which each option is perceived by
the agent in a given context. Properties can, in turn, be categorised
as either option properties (which are intrinsic to the
outcome), relational properties (which concern the outcome in
a particular context), or context properties (which concern
the context of choice itself). Such a representation permits more
detailed analysis of the reasons for an agent’s preferences and
captures different kinds of context-dependence in an agent’s
For instance, the
multiple criteria decision framework (see, for instance,
Keeney and Raiffa 1993) takes an agent’s overall preference
ordering over options to be an aggregate of the set of preference
orderings corresponding to all the pertinent dimensions of value. Under certain assumptions, the overall or aggregate preference
ordering is compatible with EU theory. One might otherwise seek to
understand the role of time, or the temporal position of goods, on
preferences. To this end, outcomes are described in terms of
temporally-indexed bundles of goods, or consumption streams
(for an early model of this kind see Ramsey 1928; a later influential
treatment is Koopmans 1960). There may be systematic structure to an
agent’s preferences over these consumption streams, over and above the
structure imposed by the EU axioms of preference.
Tacit knowledge is often used to fill the gaps in complex decision-making processes. Usually, both of these types of knowledge, tacit and explicit, are used together in the decision-making process. Early decision theorists believed that sequences of decisions made over time could be reduced to one-shot decisions among contingency plans, or strategies, but this view now has few adherents. For relevant discussions, see Peter Hammond (1988), Edward McClennen (1990), and James M. Joyce (1995). Since it is obvious that people do not typically behave in optimal ways, there is also a related area of study, which is a positive or descriptive discipline, attempting to describe what people will actually do. Since the normative, optimal decision often creates hypotheses for testing against actual behaviour, the two fields are closely linked.
This paper introduced much of the mental landscape of modern decision theory, including loss functions, risk functions, admissible decision rules, a priori distributions, Bayes decision rules, and minimax decision rules. Decision theory is an extension of probability theory, adding adds axioms and theorems to probability theory that enable mathematicians to represent decision alternatives, costs, and benefits. The intrinsic uncertainty and skewed distributions in the climate system necessitate that climate prediction be approached in a probabilistic way, e.g., [Giorgi, 2005; Schneider, 2001; 2002]. Probabilistic risk analysis (PRA) investigates the likelihood of the full range of potential outcomes [Paté-Cornell, 1996].
Behavioral Decision Theory
The prospect theory of Daniel Kahneman and Amos Tversky placed behavioural economics on a more evidence-based footing. It emphasised that in actual human (as opposed to normatively correct) decision-making « losses loom larger than gains », people are more focused on changes in their utility states than the states themselves and estimation of subjective probabilities is severely biased by anchoring. Defenders of resolute choice may have in mind a different
interpretation of sequential decision models, whereby future
“choice points” are not really points at which an agent is
free to choose according to her preferences at the time. In what follows, the standard interpretation of sequential decision
models will be assumed, and accordingly, it will be assumed that
rational agents pursue the sophisticated approach to choice (as per
Levi 1991, Maher 1992, Seidenfeld 1994, amongst others). Richard Jeffrey’s expected utility theory differs from
Savage’s in terms of both the prospects (i.e., options)
under consideration and the rationality constraints on
preferences over these prospects.
- Understanding when and under what conditions patients and family members are open to education about end-of-life choices and decision support is essential for the successful adoption of end-of-life decision support that informatics can deliver.
- There are often numerous potential trajectories of advanced cancer that are difficult to predict.
- Finally, while this section has focused on the issue of the bearing of
descriptive decision theory on its normative counterpart, it should be
noted that there has been some discussion of the converse direction of
- While such judgments are closely tied to overt choice behavior, the relationship between the two is nowhere near as direct and unsophisticated as behaviorism suggests.
- Decision theory is an extension of probability theory, adding adds axioms and theorems to probability theory that enable mathematicians to represent decision alternatives, costs, and benefits.
Second, because decision theories assume the cognitive processing of information, researchers can also obtain reports from workers about the contingencies and associations they perceive in their environments. They focus on what individuals do with the associations learned as opposed to how they are formed. Hence, researchers can be less concerned with what the environment looks like and focus on how that environment is interpreted by the workers. Decision theories have several advantages over other theories of motivation from the perspective of motivational researchers. First, as the key dependent variable, they can use self-report measures of choice rather than behavior, which can be hopelessly confounded with ability.
The Issue of Probabilistic Belief
Another example is determining when a bank should stop acquiring additional information about a borrower, and make a decision. Given the limitations of applying rigorous risk analysis to climate change policy, some advocate that we should use the precautionary principle in this situation, e.g., [Oppenheimer, 2005]. The precautionary principle prevents the use of the lack of full scientific certainty as a reason for not acting to avoid potential dangerous environmental harm. However, others argue that, although appealing in theory, the precautionary principle is impractical to implement, e.g., [Sunstein, 2002]. An application outside economics is the traffic flow problem, where cars are proceeding independently through a network of highways. In this case, we can usually expect one or more equilibrium distributions of traffic among the different highways such that no single motorist could, on average, shorten trip time by changing route as long as the others maintained their patterns.
As noted, a special case is when the content of
\(p\) is such that it is recognisably something the agent can choose
to make true, i.e., an act. The above can be taken as a preliminary characterisation of rational
preference over options. Even this limited characterisation is
contentious, however, and points to divergent interpretations of
“preferences over prospects/options”. decision theory is concerned with If the agent prefers A to B in a decision where C is not an option, then she should still prefer A to B even if C is an option, provided that C ‘s inclusion does not provide any information about state probabilities. The second principle requires each act to have a value that depends only on the values and probabilities of the outcomes it might cause.
HKT Channel – Science Theories
Of course this stability depends critically upon the assumption of perfect competition, and uniqueness is not guaranteed without additional assumptions, or anything but local optimality for each buyer and seller. Pape and Kurtz (2013) combined CBDT with the ALCOVE neural network model to analyze classification learning. In this model, the relative importance of each feature dimension is updated from feedback, with overall learning rate, aspiration level, and degree of imperfect recall estimated as model parameters. A simulated case-based agent predicted the speed of learning well across categorization schemes of various difficulty levels (Nosofsky & Palmeri, 1996; Nosofsky, Gluck, Palmeri, McKinley, & Glauthier, 1994).
Examples of their undeveloped capacities which influence decision-making would be impulse control, emotion regulation, delayed gratification and resistance to peer pressure. In the past, researchers have thought that adolescent behavior was simply due to incompetency regarding decision-making. Currently, researchers have concluded that adults and adolescents are both competent decision-makers, not just adults.
A general need exists in decision aid research to identify the optimal strategies and the appropriate timing for implementing decision aids . A critical issue for patients with terminal diagnosis is consideration of end of life, most notably the decisions of whether to continue with aggressive treatments and whether and when to enter hospice. As discussed earlier, patients often enter hospice at the very end of life during the phase of active dying.
Descriptive Decision Theory
Furthermore, facing one’s own mortality or that of a loved one can trigger anxiety or sorrow. In an effort to manage these difficult emotions, decision making with regard to end of life planning is often avoided. However, such procrastination or indecision can lead to consequences of care that are incongruent with one’s values or desires for a good death. Decision theory, which is a Bayesian approach, is concerned with identifying the values, uncertainties, and other issues relevant in a given decision and the resulting optimal decision. But, this requirement, he claimed, simply entailed that preferences
over lotteries be weakly ordered and satisfy Stochastic Dominance.
important way, at least, in which an agent can interrogate her degrees
of belief is to reflect on their pragmatic implications. Furthermore,
whether or not to seek more evidence is a pragmatic issue; it depends
on the “value of information” one expects to gain with
respect to the decision problem at hand. The idea is that seeking more
evidence is an action that is choice-worthy just in case the expected
utility of seeking further evidence before making one’s decision
is greater than the expected utility of making the decision on the
basis of existing evidence. This reasoning was made prominent in a
paper by Good (1967), where he proves that one should always seek
“free evidence” that may have a bearing on the decision at
hand. Indeed, the fact that conditionalisation plays a crucial role in
Good’s result about the non-negative value of free evidence is
taken by some as providing some justification for this learning
III.A. Classical Decision Theory
The central goal of rational choice theory is to identify the conditions under which a decision maker’s beliefs and desires rationalize the choice of an action. According to the standard model of decision-theoretic rationality, an action is rational just in case, relative to the agent’s beliefs and desires, it has the highest subjective expected utility of any available option. This subjective expected utility (SEU) theory has its roots in the work of Blaise Pascal, Daniel Bernoulli, Vilfredo Pareto, and Frank P. Ramsey, and finds its fullest expression in Leonard J. Savage’s Foundations of Statistics (1972). According to SEU a rational agent’s basic desires can be represented by a utility function u that assigns a real number u (c ) to each consequence c. The value of u (c ) measures the degree to which c would satisfy the agent’s desires and promote his or her aims.
Hence, it seems
reasonable that \(p\cup q\) should be neither strictly more nor less
desirable than both \(p\) and \(q\). Then since \(p\cup q\) is compatible
with the truth of either the more or the less desirable of the two,
\(p\cup q\)’s desirability should fall strictly between that of
\(p\) and that of \(q\). However, if \(p\) and \(q\) are equally
desirable, then \(p\cup q\) should be as desirable as each of the
- Under certain assumptions, the overall or aggregate preference
ordering is compatible with EU theory.
- Planning and decision-making process in MCDA is executed in three major phases, intelligence, design, and choice or decision (Sharifi et al., 2002) (Fig. 2).
- While decision aids exist that can allow the patient to reflect on the impact of each potential option on their own values and aid in value-concordant decision making, these have not yet blended the decision preferences of other people who may be critical to the decision-making process.
It can actually be seen as a weak version of
Independence and the Sure Thing Principle, and it plays a similar role
in Jeffrey’s theory. But it is not directly inconsistent with
Allais’ preferences, and its plausibility does not depend on the
type of probabilistic independence that the STP implies. The postulate
requires that no proposition be strictly better or worse than all of
its possible realisations, which seems to be a reasonable requirement. When \(p\) and \(q\) are mutually incompatible, \(p\cup q\) implies
that either \(p\) or \(q\) is true, but not both.