Talk:Decision theory

Decision theory vs. Detection theory

In signal processing/statistics/communications, this is known as detection theory. I don't want to say that one name is correct over the other, but I also don't want two articles heavily overlaping. It seems decision theory is geared more toward "making decisions" (1 ton of guns & 3 tons of butter vs. 2 tons of guns & 1 ton of butter) while detection theory is more about choosing/detecting (is the signal present or not?).

I think there's room for both since the technical and less-technical call them different things... Cburnett 05:24, Apr 21, 2005 (UTC)

Further point, Category:Decision theory has only one parent category: Category:Management. Cburnett 05:25, Apr 21, 2005 (UTC)

I can't see that detection/decision theory are the same at all. They cover some of the same ground, but in quite different ways; eg decision theory seems much more general (even abstract), though MCDA etc is very applied. Possibly it could be argued that detection theory is a specific application of decision theory, but I don't know enough about it to say whether that's a helpful way of putting it. Rd232 09:31, 21 Apr 2005 (UTC)

pragmatic v formal

I am at a loss as to the difference between the formal approach and the pragmatic approach to decision-making. Any ideas?

This is largely a scholarly distinction -- there is in most fields considerable room to study the theory of something without it leading to greater competence in the practical use of it. But in decision theory the question is especially well motivated, as it is unclear why one would wish to understand the theory of making decisions if it does not lead to making better decisions in practice. For most practitioners, the actual model of decision making they would choose to use in most situations would not be the perfect model, but instead a "good enough" model -- admitting at the outset that the theoretical crieria are not being fully or perfectly met for that approach to be theoretically perfect. (One often doesn't even know one's own preferences well enough to say whether the functional form of the utility function, for example, is just right.) Knowledge of the formal approach does however inform the pragmatic decision maker -- knowing that you are using an imperfect but approximate method, and knowing where you are making pragmatic compromises, is usually worth knowing. MFortunato

In the literature there is no consenus how exactly the terms 'decision theory', 'game theory' and alike are to be used. It seems important to me, though, that at least the following distinctions are kept in mind: -> 1 Person vs >1 person -> normative vs descriptive Sometimes we talk about what rational people do and hence are in the normative domain; at other times we explain or predict actual human behavious and hence are in the descriptive domain. -> Aximotic vs Interpretative Correctly applying axiomatic rules to axioms and other theorems is one thing, interpreting (parts of or the whole of) the calculus quite another. Whether or not rational choice theory really is about the right concept of rationality (if there is such a thing at all), for example, is a matter of interpretation rather than pure calculus.

'Game theory' tends to be used for >1 person-games that are interpreted in order to describe reality. 'Decision theory' tends to be used for 1- and >1-person-games, is mainly normative, and deals a lot with the issues of the right interpretation. GIV

results depends on another (but not on each other) / did you mean: results are interdependent?

If so correct the phrasing. If not, write within a parenthesis the sense in simple English.

I would have written: results are co-configured via an interdependence connectome

because the connectome is important: a. not all results are linked, b. not all results are immediately linked without intermediate stages, c. not all relationships have a single input (mono-link), d. some of the results might not connect (dump result: dump results aren't necessarily wrong if the program is [self]evolving. the perfect program tests some alterations with some dumped results, and usually few dumped results if wisely (and arbitrarily) selected are beneficial), e. some (usually few and not all) results are not interdependent (for example direct input as output, in few cases that's the correct answer)

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