Modeling Human and Organizational Behavior Application to Military Simulations (1998) / Chapter Skim
Currently Skimming:
6 Human Decision Making
6 Human Decision Making
Pages 150-171
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 150... ...
A decision is made when one of the competing alternatives is executed, producing a change in the environment and yielding consequences relevant to the decision maker. For example, in a typical decision episode, a commander under enemy fire needs to decide quickly whether to search, communicate, attack, or withdraw based on his or her current awareness of the situation.
|
From page 151... ...
The models reviewed are sufficiently formalized to provide computational models that can be used to modify existing computer simulation programs, and are at least moderately supported by empirical research. The next section illustrates one way in which individual differences and moderating states can be incorporated into decision models through the alteration of various parameters of the example decision model.
|
From page 152... ...
Expected Utility After the beginning of the eighteenth century, Bernoulli proposed a modification of expected value, called expected utility, that circumvented many of the practical problems encountered by expected-value theory. According to this
|
From page 153... ...
The justification for calling expected utility the optimal way to make decisions depends entirely on the acceptance of a small number of behavioral axioms concerning human preference. Recently, these axioms have been called into question, generating another revolution among decision theorists.
|
From page 154... ...
Rank-dependent utility can be viewed as a generalization of expected utility in the sense that rank-dependent utility theory can explain not only the same preference orders as expected utility, but others as well. The new axioms allow for the introduction of a nonlinear transformation from objective probabilities to subjective decision weights by transforming the cumulative probabilities.
|
From page 155... ...
Representing highly complex decisions in game theoretic terms may be extremely cumbersome, often requiring the use of a set of games and meta-games. Concluding Comment The utility models described in this section are idealized and deterministic with regard to the individual decision maker.
|
From page 156... ...
The second-stage models sequential sampling decision models describe the dynamic evolution of preference over time within an episode. These models provide mechanisms for explaining the effects of time pressure on decision making, as well as the relations between speed and accuracy of decisions, which are critical factors for military simulations.
|
From page 157... ...
According to a strong random-utility model, the probability of attacking will be the same for both scenarios because the payoff distributions are identical for each action within each scenario. Attacking provides an equal chance of either (85 percent damage to enemy, 0 percent damage to friendly)
|
From page 158... ...
The latter model assumes that the decision maker takes a single random sample and bases his or her decision on this single noisy estimate. The sequential sampling model assumes that the decision maker takes a sequence of random-utility estimates and integrates them over time to obtain a more precise estimate of the unknown expected utility or rank-dependent utility.
|
From page 159... ...
Not every decision takes a great deal of time or thought according to the sequential sampling model. For example, based on extensive past experience, training, instruction, or a strong status quo, the decision maker may start with a very strong initial bias, so that only a little additional information need be collected before the threshold is reached and a very quick decision is made.
|
From page 160... ...
In summary, sequential sampling models extend random-utility models to provide a dynamic description of the decision process within a single decision episode. This extension is important for explaining the effects of time pressure on decision making, as well as the relation between speed and accuracy in making a decision.
|
From page 161... ...
Therefore, the discussion in the next section is based on a synthesis of learning and decision models that provides a possible direction for building adaptive planning models for decision making. The models reviewed in this subsection are based on a synthesis of the previously described decision models and the learning models described in Chapter 5.
|
From page 162... ...
Clearly more research is needed on this important topic. INCORPORATING INDIVIDUAL DIFFERENCES AND MODERATING STATES Decision makers differ in a multitude of ways, such as risk-averse versus risk-seeking attitudes, optimistic versus pessimistic opinions, passive versus aggressive inclinations, rational versus irrational thinking, impulsive versus compulsive tendencies, and expert versus novice abilities.
|
From page 163... ...
tendencies are represented in sequential sampling models by the magnitude of the inhibitory threshold, with smaller thresholds being used by impulsive decision makers. Expert versus novice differences can be generated from an adaptive planning model by varying the amount of training that is provided with a particular decision task.
|
From page 164... ...
However, it is not clear how these phenomena might best be included in representations of human behavior for military simulations. On the one hand, if the phenomena generalize to military decision-making contexts, they will each have significant implications for both realistic representation and aiding of decision makers.
|
From page 165... ...
Again, it seems unlikely that research will produce simple generalizations of behavioral tendencies that are impervious to the effects of individual differences, context, question wording, training, and so on. Instead, research needs to address to specific settings and factors of military interest, with a view to developing locally stable understandings of phenomena appropriate for representation in models tuned to these specific situations.
|
From page 166... ...
survival rate. What needs to be investigated is whether these descriptive reframings are, in military contexts, anything more than superficial rhetorical tactics to which seasoned decision makers are impervious.
|
From page 167... ...
However two particular topics related to the learning of judgment and decision-making skills have been of interest to decision behavior researchers, and are briefly addressed here: hindsight bias and confirmatory search. The first concerns learning from one to the next in a series of decisions; the second concerns learning and information gathering within a single judgment or decision.
|
From page 168... ...
As is the case throughout this section, we intend only to suggest that dysfunctions of this sort have been found in other contexts and might well be worth seeking out and documenting in military settings as preparation for building appropriate representations into simulations of military decision makers. Proposed Research Response Research on decision behavior embraces a number of phenomena such as those reviewed above, and they presented the panel with special difficulty in forming research recommendations.
|
From page 169... ...
It is relatively easy to identify areas of obvious significance to military decision makers for which there is evidence of nonoptimal or nonintuitive behavior. However, an intensive collaboration between experts in military simulations and decision behavior researchers is needed to determine those priority problems/decision topics that the modelers see as important to their simulations and for which the behavioral researchers can identify sufficient evidence from other, nonmilitary contexts to warrant focused research.
|
From page 170... ...
· Incorporate individual differences into models by adding variability in model parameters. For example, variations in the tendency to be an impulsive versus a compulsive decision maker could be represented by variation in the threshold bound required to make a decision in sequential sampling decision models.
|
From page 171... ...
Long-Term Goals · Integrate learning with decision models to produce a synthesis that provides adaptive planning based on experience with previous episodes similar to the current situation.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.