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It is demonstrated that J. M. Keynes in 1921 provided a complete decision rule that handles both the cases of nonlinear probability preferences and ambiguity or uncertainty. The 1979 Kahneman-Tversky approach deals only with risk (non-linear probability preferences) and does not specify a decision rule. The 1985-1986 Einhorn-Hogarth anchoring and adjustment rule deals only with ambiguity or uncertainty and not risk. Only Keynes' rule does both.

It is a simple and straightforward matter to adjust the weights used in Keynes' decision theory to model risk and ambiguity aversion also to model preference for risk and ambiguity. Once these modifications are made, Keynes' theory is complete, as it covers all possible cases.

If a decision maker uses J. M. Keynes' 'conventional coefficient of risk and weight' in making decisions under conditions of risk and/or uncertainty, then a consistent pattern of ranked outcome results is not paradoxical as proposed by Allais. Similarly, the paradoxical aspects of the 'reflection effect' in Kahneman and Tversky's Prospect Theory analysis of the Allais' paradox, also vanishes. The Allais Paradox can only exist when probabilities are used in a decision-making process without a measure of confidence. By incorporating an information base for calculated probabilities the Allais Paradox results are rendered nonparadoxical.

The Ellsberg-Fellner Paradox can be shown to be nonparadoxical if Keynes' concept of weight-of-evidence is incorporated in decision making under risk and/or uncertainty. Keynes' concept is a more advanced version of C. S. Peirce's 'second number' approach and is identical to R. Carnap's reliability-unreliability index. The Ellsberg-Fellner Paradox is paradoxical only to decision theorists who accept the Von Neuman-Morgenstern-Savage axioms. Decision theorists who accept the logical approach to probability can bypass this problem.

In choice behavior, researchers have noticed that humans have a preference for some probabilities. Most researchers in the past 40 yr. have been unable to account for the nonlinearity of this behavior. The convex shape of nonlinear subjective probabilities has been experimentally confirmed by every investigator from Preston and Baratta through Edwards, Handa, and Kahneman and Tversky. What has been lacking is a clear analysis of why the probabilities have a convex shape. Here, it is argued that Keynes provided a logical explanation and a mathematical formula for this phenomenon in 1921. Had researchers not overlooked this important work, the body of knowledge on choice behavior might be more advanced.

It is demonstrated mathematically that both the expected monetary value and linear, risk-neutral, subjective, expected utility rules are special cases of J. M. Keynes' weighted monetary value rule.

Summary.-10 months following a crisis-intervention training program which focused on interpretation of signal events, 17 participants more frequently reported increased belief in their ability to recognize the need for intervention and to intervene effectively than did 22 control subjects. Perceived frequency of intervention by trained participants, however, had decreased rather than increased. Implications of the findings and recommendations for research are discussed.

Presents extensions to J.M. Keynes' decision theory. Applications in modelling risk and ambiguity aversion; Keynes' `Treatise on Probability'.

Demonstrates mathematically that the expected monetary value (EMV) and linear, risk-neutral, subjective, expected utility rules are special cases of John Maynard Keynes' theoretical approach to decision making.