Characterization of satisficing decision criterion

Matsuda, Takehiko; Takatsu, Shinzo

doi:10.1016/0020-0255(79)90036-7

Cited by 16 publications

(7 citation statements)

References 10 publications

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“…This intermediate stance takes expectations with respect to a set of probabilities; a control is justified only if it is acceptable for each expected consequence. This is similar to requirements for robustness in set-theoretic estimation, including other developments of the satisficing concept [27], [28], [40]- [43].…”

Section: B Related Literaturementioning

confidence: 64%

Model predictive satisficing fuzzy logic control

Goodrich

Stirling

Frost

1999

IEEE Trans. Fuzzy Syst.

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Section: B Related Literaturementioning

confidence: 64%

Model predictive satisficing fuzzy logic control

Goodrich

Stirling

Frost

1999

IEEE Trans. Fuzzy Syst.

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“…Put another way, to satisfice is to accept the best solution so far obtained, once the cost of continuing to search exceeds the expected improvement in value were the search to continue. Many other variations of this concept have appeared in the literature [6,13,19,22,27,28,32,34,39,49,50,[53][54][55], and it is not the intent of this paper to review them in detail. Suffice it to say, however, that all of these approaches view satisficing as a species of bounded rationality: one settles for a solution that is deemed to be "good enough," but which is not necessarily, and usually not, optimal in any meaningful sense.…”

Section: Satisficingmentioning

confidence: 99%

Satisficing Coordination and Social Welfare for Robotic Societies

Stirling

Nokleby

2008

Int J of Soc Robotics

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The design of robotic systems that are capable of sophisticated social behavior such as cooperation, compromise, negotiation, and altruism, requires more complex mathematical models than are afforded by the classical mechanisms for making value judgments and decisions. A new concept of multi-agent satisficing, defined in terms of relative effectiveness and efficiency, is an alternative to classical optimization-based decision making. Conditional utilities, which take into account the interests of others as well as the self, represent an alternative to the categorical utilities of classical decision theory. A multi-agent utility aggregation structure is developed that avoids the sure subjugation of the interests of any individual to the interests of the group. By expressing a society as a directed acyclic graph, Bayesian network theory is applied to artificial societies. A satisficing social welfare function accounts for the influence relationships among decision-making agents.

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“…A most accurate satisficing control may be considered for cases with large variations in and small variations in . Another limiting case occurs as , resulting in a least liable satisficing control, (18) This procedure is very conservative, and reflects a willingness to compromise the fundamental goal in the interest of reducing cost. It may be appropriate when there are large variations in relative to small variations in .…”

Section: Strongly Satisficing Controlmentioning

confidence: 99%

“…For these classes, the following theorems are important in developing a synthesis procedure. Recall from (17) and (18) that and are the most discriminating controls for and , respectively. Lemma 4: For continuous accuracy support and continuous liability exposure, where (19) denotes the right derivative of , and similarly define as the right derivative of .…”

Section: An Important Special Casementioning

confidence: 99%

A theory of satisficing decisions and control

Goodrich

Stirling

Frost

1998

IEEE Trans. Syst., Man, Cybern. A

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The existence of an optimal control policy and the techniques for finding it are grounded fundamentally in a global perspective. These techniques can be of limited value when the global behavior of the system is difficult to characterize, as it may be when the system is nonlinear, when the input is constrained, or when only partial information is available regarding system dynamics or the environment. Satisficing control theory is an alternative approach that is compatible with the limited rationality associated with such systems. This theory is extended by the introduction of the notion of strong satisficing to provide a systematic procedure for the design of satisficing controls. The power of the satisficing approach is illustrated by applications to representative control problems.

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Characterization of satisficing decision criterion

Cited by 16 publications

References 10 publications

Model predictive satisficing fuzzy logic control

Model predictive satisficing fuzzy logic control

Satisficing Coordination and Social Welfare for Robotic Societies

A theory of satisficing decisions and control

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