Review of A Mathematical Theory of Evidence

Zadeh, Lotfi A.

AI Magazine 

It may be argued that this, in principle, is a more realistic approach because it addresses, rather than finesses, the problem of incomplete information in the knowledge base. On the other hand, the Dempster-Shafer theory provides a basis-at least at present-for only a small subset of the rules of combination which are needed for inferencing in expert systems. In particular, the theory does not address the issue of chaining, nor does it come to grips with the fuzziness of probabilities and certainty factors. Thus, although the theory is certainly a step in the right direction, for it provides a framework for dealing with granular data, it does require a great deal of further development to become a broadly useful tool for the management of uncertainty in expert systems. Although not easy to understand, Shafer's book contains a wealth of significant results, and is a must for anyone who wants to do serious research on problems relating to the rules of combination of evidence in expert systems. Indeed, there is no doubt that, in the years to come, the Dempster-Shafer theory and its extensions will become an integral part of the theory of such systems and will certainly occupy an important place in knowledge engineering and related fields.

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