Abstract
From a certain point of view, position of every individual human being, every society, and the mankind as a whole in the surrounding world can be seen as that of the subject of a continual sequence of decision making acts, terminated by one’s death in the case of an individual, and perhaps infinite in the case of a collective agent. Just a very small portion of the decision problem we have to solve are of the deterministic nature when the consequences of the accepted decision can be completely, and with the absolute degree of certainty, foreseen so that we can choose a good, appropriate, acceptable, the best, or almost the best solution, supposing that the adjectives just introduced are sensefully, and with a sufficient degree of preciseness defined. As good examples of uncertainty-free decision procedures let us mention those ones applied in an artificial environment when any influence of uncertainty is avoided a priori. Decision-making in mathematics, or in formal systems in general, or games like chess can be remembered here. One common feature of all these cases consists in the fact that if the decision making fails, e.g., if the accepted decision is a posteriori proved not to possess the expected properties, then the only source of this failure can consist in an error made during the realization of the decision procedure (a computational error or a wrong step in a mathematical proof, for example).
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© 2001 Springer Science+Business Media New York
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Kramosil, I. (2001). Introduction. In: Probabilistic Analysis of Belief Functions. International Federation for Systems Research International Series on Systems Science and Engineering, vol 16. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0587-7_1
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DOI: https://doi.org/10.1007/978-1-4615-0587-7_1
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